Overview

Dataset statistics

Number of variables68
Number of observations437
Missing cells7911
Missing cells (%)26.6%
Total size in memory2.8 MiB
Average record size in memory6.6 KiB

Variable types

Numeric1
Text64
Unsupported3

Alerts

state_code has constant value ""Constant
se_services has constant value ""Constant
priority07 has constant value ""Constant
school_email has 41 (9.4%) missing valuesMissing
expgrade_span_min has 420 (96.1%) missing valuesMissing
expgrade_span_max has 419 (95.9%) missing valuesMissing
year_at_scale has 419 (95.9%) missing valuesMissing
subway has 80 (18.3%) missing valuesMissing
campus_name has 310 (70.9%) missing valuesMissing
school_type has 325 (74.4%) missing valuesMissing
language_classes has 27 (6.2%) missing valuesMissing
advancedplacement_courses has 124 (28.4%) missing valuesMissing
diplomaendorsements has 332 (76.0%) missing valuesMissing
psal_sports_boys has 42 (9.6%) missing valuesMissing
psal_sports_girls has 51 (11.7%) missing valuesMissing
psal_sports_coed has 303 (69.3%) missing valuesMissing
school_sports has 139 (31.8%) missing valuesMissing
partner_cbo has 73 (16.7%) missing valuesMissing
partner_hospital has 229 (52.4%) missing valuesMissing
partner_highered has 53 (12.1%) missing valuesMissing
partner_cultural has 125 (28.6%) missing valuesMissing
partner_nonprofit has 130 (29.7%) missing valuesMissing
partner_corporate has 234 (53.5%) missing valuesMissing
partner_financial has 356 (81.5%) missing valuesMissing
partner_other has 244 (55.8%) missing valuesMissing
addtl_info1 has 237 (54.2%) missing valuesMissing
addtl_info2 has 54 (12.4%) missing valuesMissing
priority02 has 80 (18.3%) missing valuesMissing
priority03 has 204 (46.7%) missing valuesMissing
priority04 has 268 (61.3%) missing valuesMissing
priority05 has 399 (91.3%) missing valuesMissing
priority06 has 418 (95.7%) missing valuesMissing
priority07 has 434 (99.3%) missing valuesMissing
priority08 has 437 (100.0%) missing valuesMissing
priority09 has 437 (100.0%) missing valuesMissing
priority10 has 437 (100.0%) missing valuesMissing
0 has unique valuesUnique
dbn has unique valuesUnique
school_name has unique valuesUnique
overview_paragraph has unique valuesUnique
priority08 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority09 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority10 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 22:18:09.595760
Analysis finished2023-12-09 22:18:13.086906
Duration3.49 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct437
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219
Minimum1
Maximum437
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-09T22:18:13.214269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.8
Q1110
median219
Q3328
95-th percentile415.2
Maximum437
Range436
Interquartile range (IQR)218

Descriptive statistics

Standard deviation126.2952889
Coefficient of variation (CV)0.5766908169
Kurtosis-1.2
Mean219
Median Absolute Deviation (MAD)109
Skewness0
Sum95703
Variance15950.5
MonotonicityStrictly increasing
2023-12-09T22:18:13.383383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
289 1
 
0.2%
300 1
 
0.2%
299 1
 
0.2%
298 1
 
0.2%
297 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
293 1
 
0.2%
Other values (427) 427
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
ValueCountFrequency (%)
437 1
0.2%
436 1
0.2%
435 1
0.2%
434 1
0.2%
433 1
0.2%

dbn
Text

UNIQUE 

Distinct437
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2023-12-09T22:18:13.792711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2622
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique437 ?
Unique (%)100.0%

Sample

1st row01M292
2nd row01M448
3rd row01M450
4th row01M509
5th row01M539
ValueCountFrequency (%)
31r600 1
 
0.2%
06m348 1
 
0.2%
03m479 1
 
0.2%
13k499 1
 
0.2%
07x223 1
 
0.2%
20k505 1
 
0.2%
02m500 1
 
0.2%
29q283 1
 
0.2%
13k350 1
 
0.2%
30q301 1
 
0.2%
Other values (427) 427
97.7%
2023-12-09T22:18:14.351091image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 346
13.2%
0 331
12.6%
1 269
10.3%
4 251
9.6%
5 248
9.5%
3 200
7.6%
6 153
 
5.8%
9 140
 
5.3%
8 126
 
4.8%
7 121
 
4.6%
Other values (5) 437
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2185
83.3%
Uppercase Letter 437
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 346
15.8%
0 331
15.1%
1 269
12.3%
4 251
11.5%
5 248
11.4%
3 200
9.2%
6 153
7.0%
9 140
6.4%
8 126
 
5.8%
7 121
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
K 121
27.7%
X 119
27.2%
M 107
24.5%
Q 80
18.3%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2185
83.3%
Latin 437
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 346
15.8%
0 331
15.1%
1 269
12.3%
4 251
11.5%
5 248
11.4%
3 200
9.2%
6 153
7.0%
9 140
6.4%
8 126
 
5.8%
7 121
 
5.5%
Latin
ValueCountFrequency (%)
K 121
27.7%
X 119
27.2%
M 107
24.5%
Q 80
18.3%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 346
13.2%
0 331
12.6%
1 269
10.3%
4 251
9.6%
5 248
9.5%
3 200
7.6%
6 153
 
5.8%
9 140
 
5.3%
8 126
 
4.8%
7 121
 
4.6%
Other values (5) 437
16.7%

school_name
Text

UNIQUE 

Distinct437
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size40.2 KiB
2023-12-09T22:18:14.761418image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length57
Mean length36.90389016
Min length11

Characters and Unicode

Total characters16127
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique437 ?
Unique (%)100.0%

Sample

1st rowHenry Street School for International Studies
2nd rowUniversity Neighborhood High School
3rd rowEast Side Community School
4th rowMarta Valle High School
5th rowNew Explorations into Science, Technology and Math High School
ValueCountFrequency (%)
school 341
 
14.3%
high 231
 
9.7%
for 136
 
5.7%
academy 102
 
4.3%
and 96
 
4.0%
the 58
 
2.4%
of 57
 
2.4%
bronx 38
 
1.6%
college 37
 
1.5%
arts 37
 
1.5%
Other values (506) 1259
52.6%
2023-12-09T22:18:15.357257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1955
 
12.1%
o 1509
 
9.4%
e 1120
 
6.9%
a 919
 
5.7%
n 842
 
5.2%
r 832
 
5.2%
i 829
 
5.1%
l 817
 
5.1%
h 810
 
5.0%
c 757
 
4.7%
Other values (60) 5737
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11735
72.8%
Uppercase Letter 2280
 
14.1%
Space Separator 1955
 
12.1%
Other Punctuation 121
 
0.8%
Decimal Number 17
 
0.1%
Dash Punctuation 7
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1509
12.9%
e 1120
9.5%
a 919
 
7.8%
n 842
 
7.2%
r 832
 
7.1%
i 829
 
7.1%
l 817
 
7.0%
h 810
 
6.9%
c 757
 
6.5%
t 554
 
4.7%
Other values (16) 2746
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 479
21.0%
H 310
13.6%
A 237
10.4%
C 176
 
7.7%
T 119
 
5.2%
B 111
 
4.9%
E 105
 
4.6%
M 97
 
4.3%
L 89
 
3.9%
P 81
 
3.6%
Other values (16) 476
20.9%
Decimal Number
ValueCountFrequency (%)
2 4
23.5%
3 3
17.6%
6 2
11.8%
4 2
11.8%
7 2
11.8%
1 2
11.8%
8 1
 
5.9%
0 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 41
33.9%
, 38
31.4%
: 16
 
13.2%
& 15
 
12.4%
' 7
 
5.8%
/ 4
 
3.3%
Space Separator
ValueCountFrequency (%)
1955
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14015
86.9%
Common 2112
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1509
 
10.8%
e 1120
 
8.0%
a 919
 
6.6%
n 842
 
6.0%
r 832
 
5.9%
i 829
 
5.9%
l 817
 
5.8%
h 810
 
5.8%
c 757
 
5.4%
t 554
 
4.0%
Other values (42) 5026
35.9%
Common
ValueCountFrequency (%)
1955
92.6%
. 41
 
1.9%
, 38
 
1.8%
: 16
 
0.8%
& 15
 
0.7%
- 7
 
0.3%
' 7
 
0.3%
) 6
 
0.3%
( 6
 
0.3%
2 4
 
0.2%
Other values (8) 17
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1955
 
12.1%
o 1509
 
9.4%
e 1120
 
6.9%
a 919
 
5.7%
n 842
 
5.2%
r 832
 
5.2%
i 829
 
5.1%
l 817
 
5.1%
h 810
 
5.0%
c 757
 
4.7%
Other values (60) 5737
35.6%

boro
Text

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size27.5 KiB
2023-12-09T22:18:15.553616image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.176201373
Min length5

Characters and Unicode

Total characters3136
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowManhattan
3rd rowManhattan
4th rowManhattan
5th rowManhattan
ValueCountFrequency (%)
brooklyn 121
27.1%
bronx 119
26.6%
manhattan 107
23.9%
queens 80
17.9%
staten 10
 
2.2%
island 10
 
2.2%
2023-12-09T22:18:15.877573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 554
17.7%
o 361
11.5%
a 341
10.9%
B 240
 
7.7%
r 240
 
7.7%
t 234
 
7.5%
e 170
 
5.4%
l 131
 
4.2%
k 121
 
3.9%
y 121
 
3.9%
Other values (10) 623
19.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2679
85.4%
Uppercase Letter 447
 
14.3%
Space Separator 10
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 554
20.7%
o 361
13.5%
a 341
12.7%
r 240
9.0%
t 234
8.7%
e 170
 
6.3%
l 131
 
4.9%
k 121
 
4.5%
y 121
 
4.5%
x 119
 
4.4%
Other values (4) 287
10.7%
Uppercase Letter
ValueCountFrequency (%)
B 240
53.7%
M 107
23.9%
Q 80
 
17.9%
S 10
 
2.2%
I 10
 
2.2%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3126
99.7%
Common 10
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 554
17.7%
o 361
11.5%
a 341
10.9%
B 240
 
7.7%
r 240
 
7.7%
t 234
 
7.5%
e 170
 
5.4%
l 131
 
4.2%
k 121
 
3.9%
y 121
 
3.9%
Other values (9) 613
19.6%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 554
17.7%
o 361
11.5%
a 341
10.9%
B 240
 
7.7%
r 240
 
7.7%
t 234
 
7.5%
e 170
 
5.4%
l 131
 
4.2%
k 121
 
3.9%
y 121
 
3.9%
Other values (10) 623
19.9%
Distinct258
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size26.2 KiB
2023-12-09T22:18:16.396165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1748
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)40.3%

Sample

1st rowM056
2nd rowM446
3rd rowM060
4th rowM025
5th rowM022
ValueCountFrequency (%)
x410 6
 
1.4%
x450 6
 
1.4%
x405 6
 
1.4%
x425 6
 
1.4%
x435 6
 
1.4%
x415 5
 
1.1%
m445 5
 
1.1%
k465 5
 
1.1%
m440 5
 
1.1%
m490 5
 
1.1%
Other values (248) 382
87.4%
2023-12-09T22:18:17.042324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 270
15.4%
0 256
14.6%
5 200
11.4%
K 121
 
6.9%
X 119
 
6.8%
M 107
 
6.1%
6 104
 
5.9%
2 91
 
5.2%
1 86
 
4.9%
3 81
 
4.6%
Other values (5) 313
17.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1311
75.0%
Uppercase Letter 437
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 270
20.6%
0 256
19.5%
5 200
15.3%
6 104
 
7.9%
2 91
 
6.9%
1 86
 
6.6%
3 81
 
6.2%
7 79
 
6.0%
8 78
 
5.9%
9 66
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
K 121
27.7%
X 119
27.2%
M 107
24.5%
Q 80
18.3%
R 10
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1311
75.0%
Latin 437
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 270
20.6%
0 256
19.5%
5 200
15.3%
6 104
 
7.9%
2 91
 
6.9%
1 86
 
6.6%
3 81
 
6.2%
7 79
 
6.0%
8 78
 
5.9%
9 66
 
5.0%
Latin
ValueCountFrequency (%)
K 121
27.7%
X 119
27.2%
M 107
24.5%
Q 80
18.3%
R 10
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1748
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 270
15.4%
0 256
14.6%
5 200
11.4%
K 121
 
6.9%
X 119
 
6.8%
M 107
 
6.1%
6 104
 
5.9%
2 91
 
5.2%
1 86
 
4.9%
3 81
 
4.6%
Other values (5) 313
17.9%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
2023-12-09T22:18:17.188389image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.842105263
Min length2

Characters and Unicode

Total characters1242
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
yes 368
84.2%
no 69
 
15.8%
2023-12-09T22:18:17.460935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 368
29.6%
e 368
29.6%
s 368
29.6%
N 69
 
5.6%
o 69
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 805
64.8%
Uppercase Letter 437
35.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 368
45.7%
s 368
45.7%
o 69
 
8.6%
Uppercase Letter
ValueCountFrequency (%)
Y 368
84.2%
N 69
 
15.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 1242
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 368
29.6%
e 368
29.6%
s 368
29.6%
N 69
 
5.6%
o 69
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 368
29.6%
e 368
29.6%
s 368
29.6%
N 69
 
5.6%
o 69
 
5.6%
Distinct431
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
2023-12-09T22:18:17.764107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5244
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique428 ?
Unique (%)97.9%

Sample

1st row212-406-9411
2nd row212-962-4341
3rd row212-460-8467
4th row212-473-8152
5th row212-677-5190
ValueCountFrequency (%)
718-381-7100 4
 
0.9%
212-927-1841 3
 
0.7%
718-387-2800 2
 
0.5%
718-402-7690 1
 
0.2%
718-621-8800 1
 
0.2%
718-589-1590 1
 
0.2%
212-757-2680 1
 
0.2%
718-271-1487 1
 
0.2%
212-677-5190 1
 
0.2%
212-501-3318 1
 
0.2%
Other values (421) 421
96.3%
2023-12-09T22:18:18.211806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 874
16.7%
1 714
13.6%
8 624
11.9%
7 597
11.4%
2 548
10.5%
0 457
8.7%
3 326
 
6.2%
4 293
 
5.6%
6 292
 
5.6%
5 273
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4370
83.3%
Dash Punctuation 874
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 714
16.3%
8 624
14.3%
7 597
13.7%
2 548
12.5%
0 457
10.5%
3 326
7.5%
4 293
6.7%
6 292
6.7%
5 273
 
6.2%
9 246
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 874
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 874
16.7%
1 714
13.6%
8 624
11.9%
7 597
11.4%
2 548
10.5%
0 457
8.7%
3 326
 
6.2%
4 293
 
5.6%
6 292
 
5.6%
5 273
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 874
16.7%
1 714
13.6%
8 624
11.9%
7 597
11.4%
2 548
10.5%
0 457
8.7%
3 326
 
6.2%
4 293
 
5.6%
6 292
 
5.6%
5 273
 
5.2%
Distinct432
Distinct (%)99.8%
Missing4
Missing (%)0.9%
Memory size29.4 KiB
2023-12-09T22:18:18.527463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5196
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique431 ?
Unique (%)99.5%

Sample

1st row212-406-9417
2nd row212-267-5611
3rd row212-260-9657
4th row212-475-7588
5th row212-260-8124
ValueCountFrequency (%)
212-674-8021 2
 
0.5%
718-681-8650 1
 
0.2%
718-564-2567 1
 
0.2%
917-441-3693 1
 
0.2%
718-525-6276 1
 
0.2%
718-815-9638 1
 
0.2%
718-946-5035 1
 
0.2%
718-387-2748 1
 
0.2%
212-691-2147 1
 
0.2%
718-370-6915 1
 
0.2%
Other values (422) 422
97.5%
2023-12-09T22:18:18.960559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 866
16.7%
1 693
13.3%
7 636
12.2%
8 622
12.0%
2 570
11.0%
6 334
 
6.4%
3 330
 
6.4%
5 319
 
6.1%
9 303
 
5.8%
4 288
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4330
83.3%
Dash Punctuation 866
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 693
16.0%
7 636
14.7%
8 622
14.4%
2 570
13.2%
6 334
7.7%
3 330
7.6%
5 319
7.4%
9 303
7.0%
4 288
6.7%
0 235
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 866
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5196
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 866
16.7%
1 693
13.3%
7 636
12.2%
8 622
12.0%
2 570
11.0%
6 334
 
6.4%
3 330
 
6.4%
5 319
 
6.1%
9 303
 
5.8%
4 288
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 866
16.7%
1 693
13.3%
7 636
12.2%
8 622
12.0%
2 570
11.0%
6 334
 
6.4%
3 330
 
6.4%
5 319
 
6.1%
9 303
 
5.8%
4 288
 
5.5%

school_email
Text

MISSING 

Distinct396
Distinct (%)100.0%
Missing41
Missing (%)9.4%
Memory size32.7 KiB
2023-12-09T22:18:19.269564image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length48
Mean length23.82323232
Min length13

Characters and Unicode

Total characters9434
Distinct characters69
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique396 ?
Unique (%)100.0%

Sample

1st rowcloughl@schools.nyc.gov
2nd rowransonunhs@gmail.com
3rd rowtomm@eschs.org
4th rowjbailey2@schools.nyc.gov
5th rowSglasgall@schools.nyc.gov
ValueCountFrequency (%)
dmorris4@schools.nyc.gov 1
 
0.2%
gmartor@schools.nyc.gov 1
 
0.2%
kalfano@schools.nyc.gov 1
 
0.2%
jbloomb@schools.nyc.gov 1
 
0.2%
mritter1@schools.nyc.gov 1
 
0.2%
knorman3@schools.nyc.gov 1
 
0.2%
mpanindranauth@schools.nyc.gov 1
 
0.2%
herohighadmissions@gmail.com 1
 
0.2%
archimedesacademy@gmail.com 1
 
0.2%
info@bronxacademy.org 1
 
0.2%
Other values (392) 392
97.5%
2023-12-09T22:18:19.736728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1226
 
13.0%
s 804
 
8.5%
c 752
 
8.0%
. 659
 
7.0%
n 600
 
6.4%
l 497
 
5.3%
g 461
 
4.9%
h 432
 
4.6%
@ 401
 
4.3%
a 395
 
4.2%
Other values (59) 3207
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7821
82.9%
Other Punctuation 1072
 
11.4%
Decimal Number 307
 
3.3%
Uppercase Letter 220
 
2.3%
Space Separator 6
 
0.1%
Dash Punctuation 6
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1226
15.7%
s 804
10.3%
c 752
 
9.6%
n 600
 
7.7%
l 497
 
6.4%
g 461
 
5.9%
h 432
 
5.5%
a 395
 
5.1%
r 353
 
4.5%
y 338
 
4.3%
Other values (16) 1963
25.1%
Uppercase Letter
ValueCountFrequency (%)
M 24
 
10.9%
S 21
 
9.5%
K 16
 
7.3%
C 15
 
6.8%
R 14
 
6.4%
D 13
 
5.9%
H 12
 
5.5%
G 11
 
5.0%
A 11
 
5.0%
Q 9
 
4.1%
Other values (15) 74
33.6%
Decimal Number
ValueCountFrequency (%)
2 72
23.5%
4 46
15.0%
1 37
12.1%
3 33
10.7%
0 32
10.4%
5 25
 
8.1%
7 21
 
6.8%
6 20
 
6.5%
8 12
 
3.9%
9 9
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 659
61.5%
@ 401
37.4%
; 6
 
0.6%
/ 5
 
0.5%
: 1
 
0.1%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8041
85.2%
Common 1393
 
14.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1226
15.2%
s 804
 
10.0%
c 752
 
9.4%
n 600
 
7.5%
l 497
 
6.2%
g 461
 
5.7%
h 432
 
5.4%
a 395
 
4.9%
r 353
 
4.4%
y 338
 
4.2%
Other values (41) 2183
27.1%
Common
ValueCountFrequency (%)
. 659
47.3%
@ 401
28.8%
2 72
 
5.2%
4 46
 
3.3%
1 37
 
2.7%
3 33
 
2.4%
0 32
 
2.3%
5 25
 
1.8%
7 21
 
1.5%
6 20
 
1.4%
Other values (8) 47
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1226
 
13.0%
s 804
 
8.5%
c 752
 
8.0%
. 659
 
7.0%
n 600
 
6.4%
l 497
 
5.3%
g 461
 
4.9%
h 432
 
4.6%
@ 401
 
4.3%
a 395
 
4.2%
Other values (59) 3207
34.0%
Distinct3
Distinct (%)0.7%
Missing3
Missing (%)0.7%
Memory size24.8 KiB
2023-12-09T22:18:19.868095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters434
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row6
2nd row9
3rd row6
4th row9
5th row9
ValueCountFrequency (%)
9 351
80.9%
6 82
 
18.9%
7 1
 
0.2%
2023-12-09T22:18:20.110703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 351
80.9%
6 82
 
18.9%
7 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 434
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 351
80.9%
6 82
 
18.9%
7 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 434
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 351
80.9%
6 82
 
18.9%
7 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 351
80.9%
6 82
 
18.9%
7 1
 
0.2%
Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
2023-12-09T22:18:20.269898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.99771167
Min length1

Characters and Unicode

Total characters873
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12
ValueCountFrequency (%)
12 422
96.6%
11 10
 
2.3%
10 3
 
0.7%
14 1
 
0.2%
9 1
 
0.2%
2023-12-09T22:18:20.533229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 446
51.1%
2 422
48.3%
0 3
 
0.3%
4 1
 
0.1%
9 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 873
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 446
51.1%
2 422
48.3%
0 3
 
0.3%
4 1
 
0.1%
9 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 446
51.1%
2 422
48.3%
0 3
 
0.3%
4 1
 
0.1%
9 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 446
51.1%
2 422
48.3%
0 3
 
0.3%
4 1
 
0.1%
9 1
 
0.1%

expgrade_span_min
Text

MISSING 

Distinct2
Distinct (%)11.8%
Missing420
Missing (%)96.1%
Memory size14.2 KiB
2023-12-09T22:18:20.653035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters17
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row9
3rd row9
4th row6
5th row9
ValueCountFrequency (%)
9 12
70.6%
6 5
29.4%
2023-12-09T22:18:20.893653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 12
70.6%
6 5
29.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 12
70.6%
6 5
29.4%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 12
70.6%
6 5
29.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 12
70.6%
6 5
29.4%

expgrade_span_max
Text

MISSING 

Distinct2
Distinct (%)11.1%
Missing419
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:18:21.032036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters36
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row14
3rd row12
4th row12
5th row14
ValueCountFrequency (%)
12 12
66.7%
14 6
33.3%
2023-12-09T22:18:21.285645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
50.0%
2 12
33.3%
4 6
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
50.0%
2 12
33.3%
4 6
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
50.0%
2 12
33.3%
4 6
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
50.0%
2 12
33.3%
4 6
 
16.7%

year_at_scale
Text

MISSING 

Distinct4
Distinct (%)22.2%
Missing419
Missing (%)95.9%
Memory size14.3 KiB
2023-12-09T22:18:21.441027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters72
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)5.6%

Sample

1st row2018
2nd row2019
3rd row2017
4th row2019
5th row2019
ValueCountFrequency (%)
2017 7
38.9%
2018 5
27.8%
2019 5
27.8%
2020 1
 
5.6%
2023-12-09T22:18:21.718133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19
26.4%
0 19
26.4%
1 17
23.6%
7 7
 
9.7%
8 5
 
6.9%
9 5
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19
26.4%
0 19
26.4%
1 17
23.6%
7 7
 
9.7%
8 5
 
6.9%
9 5
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
Common 72
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19
26.4%
0 19
26.4%
1 17
23.6%
7 7
 
9.7%
8 5
 
6.9%
9 5
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19
26.4%
0 19
26.4%
1 17
23.6%
7 7
 
9.7%
8 5
 
6.9%
9 5
 
6.9%

bus
Text

Distinct244
Distinct (%)56.2%
Missing3
Missing (%)0.7%
Memory size44.8 KiB
2023-12-09T22:18:22.260888image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length208
Median length106
Mean length48.21658986
Min length8

Characters and Unicode

Total characters20926
Distinct characters22
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)36.2%

Sample

1st rowB39, M14A, M14D, M15, M15-SBS, M21, M22, M9
2nd rowM14A, M14D, M15, M21, M22, M9
3rd rowM1, M101, M102, M103, M14A, M14D, M15, M15-SBS, M23, M3, M8, M9
4th rowB39, M103, M14A, M14D, M15, M15-SBS, M21, M22, M8, M9
5th rowB39, M14A, M14D, M21, M22, M8, M9
ValueCountFrequency (%)
m5 57
 
1.4%
bx15 49
 
1.2%
bx41 47
 
1.2%
bx1 46
 
1.1%
bxm4 45
 
1.1%
m15 45
 
1.1%
bx17 45
 
1.1%
m101 45
 
1.1%
x28 44
 
1.1%
m15-sbs 44
 
1.1%
Other values (282) 3601
88.5%
2023-12-09T22:18:23.010881image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 3634
17.4%
3634
17.4%
B 2143
10.2%
1 1795
8.6%
M 1299
 
6.2%
x 1156
 
5.5%
2 946
 
4.5%
4 937
 
4.5%
3 740
 
3.5%
Q 728
 
3.5%
Other values (12) 3914
18.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7381
35.3%
Uppercase Letter 4997
23.9%
Other Punctuation 3634
17.4%
Space Separator 3634
17.4%
Lowercase Letter 1156
 
5.5%
Dash Punctuation 124
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1795
24.3%
2 946
12.8%
4 937
12.7%
3 740
10.0%
5 605
 
8.2%
6 598
 
8.1%
0 584
 
7.9%
7 462
 
6.3%
8 412
 
5.6%
9 302
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 2143
42.9%
M 1299
26.0%
Q 728
 
14.6%
X 388
 
7.8%
S 309
 
6.2%
A 98
 
2.0%
D 30
 
0.6%
J 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 3634
100.0%
Space Separator
ValueCountFrequency (%)
3634
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 1156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14773
70.6%
Latin 6153
29.4%

Most frequent character per script

Common
ValueCountFrequency (%)
, 3634
24.6%
3634
24.6%
1 1795
12.2%
2 946
 
6.4%
4 937
 
6.3%
3 740
 
5.0%
5 605
 
4.1%
6 598
 
4.0%
0 584
 
4.0%
7 462
 
3.1%
Other values (3) 838
 
5.7%
Latin
ValueCountFrequency (%)
B 2143
34.8%
M 1299
21.1%
x 1156
18.8%
Q 728
 
11.8%
X 388
 
6.3%
S 309
 
5.0%
A 98
 
1.6%
D 30
 
0.5%
J 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 3634
17.4%
3634
17.4%
B 2143
10.2%
1 1795
8.6%
M 1299
 
6.2%
x 1156
 
5.5%
2 946
 
4.5%
4 937
 
4.5%
3 740
 
3.5%
Q 728
 
3.5%
Other values (12) 3914
18.7%

subway
Text

MISSING 

Distinct193
Distinct (%)54.1%
Missing80
Missing (%)18.3%
Memory size39.8 KiB
2023-12-09T22:18:23.394835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length215
Median length111
Mean length49.58263305
Min length12

Characters and Unicode

Total characters17701
Distinct characters68
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)34.2%

Sample

1st rowF to East Broadway ; B, D to Grand St ; J, M, Z to Delancey St-Essex St
2nd rowJ, M, Z to Delancey St-Essex St ; F to East Broadway
3rd row6 to Astor Place ; L to 1st Ave
4th rowB, D to Grand St ; F, J, M, Z to Delancey St-Essex St
5th rowF, J, M, Z to Delancey St-Essex St
ValueCountFrequency (%)
to 734
 
16.0%
478
 
10.4%
st 327
 
7.1%
ave 198
 
4.3%
2 124
 
2.7%
5 109
 
2.4%
b 106
 
2.3%
d 91
 
2.0%
a 87
 
1.9%
c 87
 
1.9%
Other values (301) 2235
48.8%
2023-12-09T22:18:23.959859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4219
23.8%
t 1762
 
10.0%
o 1134
 
6.4%
, 807
 
4.6%
e 786
 
4.4%
a 547
 
3.1%
r 546
 
3.1%
S 545
 
3.1%
n 459
 
2.6%
h 397
 
2.2%
Other values (58) 6499
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8005
45.2%
Space Separator 4219
23.8%
Uppercase Letter 2653
 
15.0%
Decimal Number 1356
 
7.7%
Other Punctuation 1201
 
6.8%
Dash Punctuation 267
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 545
20.5%
A 330
12.4%
B 215
 
8.1%
C 207
 
7.8%
M 126
 
4.7%
R 120
 
4.5%
D 118
 
4.4%
F 113
 
4.3%
L 99
 
3.7%
G 97
 
3.7%
Other values (16) 683
25.7%
Lowercase Letter
ValueCountFrequency (%)
t 1762
22.0%
o 1134
14.2%
e 786
9.8%
a 547
 
6.8%
r 546
 
6.8%
n 459
 
5.7%
h 397
 
5.0%
l 329
 
4.1%
s 268
 
3.3%
v 267
 
3.3%
Other values (15) 1510
18.9%
Decimal Number
ValueCountFrequency (%)
1 255
18.8%
2 201
14.8%
5 186
13.7%
4 181
13.3%
3 167
12.3%
6 137
10.1%
7 74
 
5.5%
9 60
 
4.4%
8 50
 
3.7%
0 45
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 807
67.2%
; 377
31.4%
& 11
 
0.9%
' 3
 
0.2%
/ 3
 
0.2%
Space Separator
ValueCountFrequency (%)
4219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 267
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10658
60.2%
Common 7043
39.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1762
16.5%
o 1134
 
10.6%
e 786
 
7.4%
a 547
 
5.1%
r 546
 
5.1%
S 545
 
5.1%
n 459
 
4.3%
h 397
 
3.7%
A 330
 
3.1%
l 329
 
3.1%
Other values (41) 3823
35.9%
Common
ValueCountFrequency (%)
4219
59.9%
, 807
 
11.5%
; 377
 
5.4%
- 267
 
3.8%
1 255
 
3.6%
2 201
 
2.9%
5 186
 
2.6%
4 181
 
2.6%
3 167
 
2.4%
6 137
 
1.9%
Other values (7) 246
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17701
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4219
23.8%
t 1762
 
10.0%
o 1134
 
6.4%
, 807
 
4.6%
e 786
 
4.4%
a 547
 
3.1%
r 546
 
3.1%
S 545
 
3.1%
n 459
 
2.6%
h 397
 
2.2%
Other values (58) 6499
36.7%
Distinct258
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
2023-12-09T22:18:24.344566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length26
Mean length18.92677346
Min length11

Characters and Unicode

Total characters8271
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)40.3%

Sample

1st row220 HENRY STREET
2nd row200 MONROE STREET
3rd row420 EAST 12 STREET
4th row145 STANTON STREET
5th row111 COLUMBIA STREET
ValueCountFrequency (%)
avenue 187
 
12.8%
street 163
 
11.1%
east 55
 
3.8%
west 48
 
3.3%
road 27
 
1.8%
boulevard 13
 
0.9%
place 12
 
0.8%
drive 9
 
0.6%
grand 9
 
0.6%
350 9
 
0.6%
Other values (453) 933
63.7%
2023-12-09T22:18:24.857483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1041
 
12.6%
1029
 
12.4%
T 637
 
7.7%
A 546
 
6.6%
S 412
 
5.0%
N 408
 
4.9%
R 395
 
4.8%
0 351
 
4.2%
1 338
 
4.1%
U 254
 
3.1%
Other values (29) 2860
34.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5352
64.7%
Decimal Number 1795
 
21.7%
Space Separator 1029
 
12.4%
Dash Punctuation 83
 
1.0%
Other Punctuation 12
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1041
19.5%
T 637
11.9%
A 546
10.2%
S 412
 
7.7%
N 408
 
7.6%
R 395
 
7.4%
U 254
 
4.7%
V 246
 
4.6%
O 242
 
4.5%
L 154
 
2.9%
Other values (14) 1017
19.0%
Decimal Number
ValueCountFrequency (%)
0 351
19.6%
1 338
18.8%
2 205
11.4%
5 199
11.1%
3 162
9.0%
4 148
8.2%
6 102
 
5.7%
9 101
 
5.6%
7 99
 
5.5%
8 90
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 10
83.3%
' 1
 
8.3%
, 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5352
64.7%
Common 2919
35.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1041
19.5%
T 637
11.9%
A 546
10.2%
S 412
 
7.7%
N 408
 
7.6%
R 395
 
7.4%
U 254
 
4.7%
V 246
 
4.6%
O 242
 
4.5%
L 154
 
2.9%
Other values (14) 1017
19.0%
Common
ValueCountFrequency (%)
1029
35.3%
0 351
 
12.0%
1 338
 
11.6%
2 205
 
7.0%
5 199
 
6.8%
3 162
 
5.5%
4 148
 
5.1%
6 102
 
3.5%
9 101
 
3.5%
7 99
 
3.4%
Other values (5) 185
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 1041
 
12.6%
1029
 
12.4%
T 637
 
7.7%
A 546
 
6.6%
S 412
 
5.0%
N 408
 
4.9%
R 395
 
4.8%
0 351
 
4.2%
1 338
 
4.1%
U 254
 
3.1%
Other values (29) 2860
34.6%

city
Text

Distinct9
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size28.0 KiB
2023-12-09T22:18:25.052442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.208237986
Min length6

Characters and Unicode

Total characters3587
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.7%

Sample

1st row MANHATTAN
2nd row MANHATTAN
3rd row MANHATTAN
4th row MANHATTAN
5th row MANHATTAN
ValueCountFrequency (%)
brooklyn 121
26.9%
bronx 119
26.4%
manhattan 106
23.6%
queens 74
16.4%
island 11
 
2.4%
staten 10
 
2.2%
jamaica 4
 
0.9%
bayside 1
 
0.2%
long 1
 
0.2%
city 1
 
0.2%
Other values (2) 2
 
0.4%
2023-12-09T22:18:25.363592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
15.3%
450
12.5%
O 363
10.1%
A 352
9.8%
R 241
 
6.7%
B 241
 
6.7%
T 233
 
6.5%
E 160
 
4.5%
L 133
 
3.7%
Y 124
 
3.5%
Other values (13) 741
20.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3137
87.5%
Space Separator 450
 
12.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
17.5%
O 363
11.6%
A 352
11.2%
R 241
 
7.7%
B 241
 
7.7%
T 233
 
7.4%
E 160
 
5.1%
L 133
 
4.2%
Y 124
 
4.0%
K 122
 
3.9%
Other values (12) 619
19.7%
Space Separator
ValueCountFrequency (%)
450
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3137
87.5%
Common 450
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
17.5%
O 363
11.6%
A 352
11.2%
R 241
 
7.7%
B 241
 
7.7%
T 233
 
7.4%
E 160
 
5.1%
L 133
 
4.2%
Y 124
 
4.0%
K 122
 
3.9%
Other values (12) 619
19.7%
Common
ValueCountFrequency (%)
450
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3587
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
15.3%
450
12.5%
O 363
10.1%
A 352
9.8%
R 241
 
6.7%
B 241
 
6.7%
T 233
 
6.5%
E 160
 
4.5%
L 133
 
3.7%
Y 124
 
3.5%
Other values (13) 741
20.7%

state_code
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.3 KiB
2023-12-09T22:18:25.474749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters874
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNY
2nd rowNY
3rd rowNY
4th rowNY
5th rowNY
ValueCountFrequency (%)
ny 437
100.0%
2023-12-09T22:18:25.689648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 437
50.0%
Y 437
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 874
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 437
50.0%
Y 437
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 874
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 437
50.0%
Y 437
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 437
50.0%
Y 437
50.0%

zip
Text

Distinct120
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size26.6 KiB
2023-12-09T22:18:26.081914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2185
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)8.7%

Sample

1st row10002
2nd row10002
3rd row10009
4th row10002
5th row10002
ValueCountFrequency (%)
10457 13
 
3.0%
11101 12
 
2.7%
11201 11
 
2.5%
10456 11
 
2.5%
10002 11
 
2.5%
10468 10
 
2.3%
10019 10
 
2.3%
10451 9
 
2.1%
10458 9
 
2.1%
11208 9
 
2.1%
Other values (110) 332
76.0%
2023-12-09T22:18:26.601902image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 808
37.0%
0 459
21.0%
2 212
 
9.7%
4 192
 
8.8%
3 154
 
7.0%
6 115
 
5.3%
5 100
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2185
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 808
37.0%
0 459
21.0%
2 212
 
9.7%
4 192
 
8.8%
3 154
 
7.0%
6 115
 
5.3%
5 100
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2185
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 808
37.0%
0 459
21.0%
2 212
 
9.7%
4 192
 
8.8%
3 154
 
7.0%
6 115
 
5.3%
5 100
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 808
37.0%
0 459
21.0%
2 212
 
9.7%
4 192
 
8.8%
3 154
 
7.0%
6 115
 
5.3%
5 100
 
4.6%
7 67
 
3.1%
8 40
 
1.8%
9 38
 
1.7%
Distinct435
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size36.0 KiB
2023-12-09T22:18:26.905355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length35
Mean length27.00915332
Min length11

Characters and Unicode

Total characters11803
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique433 ?
Unique (%)99.1%

Sample

1st rowhttp://schools.nyc.gov/SchoolPortals/01/M292
2nd rowwww.universityneighborhoodhs.org
3rd rowwww.eschs.org
4th rowwww.martavalle.org
5th rowwww.nestmk12.net
ValueCountFrequency (%)
www.epicschoolsnyc.org 2
 
0.5%
www.bard.edu/bhsec 2
 
0.5%
www.nycmuseumschool.org 1
 
0.2%
www.greenschoolbrooklyn.com 1
 
0.2%
www.williamsburgprep.com 1
 
0.2%
http://schools.nyc.gov/schoolportals/26/q435 1
 
0.2%
thehssm.com 1
 
0.2%
www.bxdca.org 1
 
0.2%
www.queenscollegiate.wordpress.com 1
 
0.2%
www.newtownhighschool.org 1
 
0.2%
Other values (425) 425
97.3%
2023-12-09T22:18:27.364357image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1323
 
11.2%
w 966
 
8.2%
. 877
 
7.4%
s 725
 
6.1%
c 682
 
5.8%
h 658
 
5.6%
/ 656
 
5.6%
l 589
 
5.0%
t 570
 
4.8%
r 550
 
4.7%
Other values (54) 4207
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8988
76.2%
Other Punctuation 1665
 
14.1%
Decimal Number 680
 
5.8%
Uppercase Letter 462
 
3.9%
Dash Punctuation 8
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1323
14.7%
w 966
10.7%
s 725
 
8.1%
c 682
 
7.6%
h 658
 
7.3%
l 589
 
6.6%
t 570
 
6.3%
r 550
 
6.1%
g 425
 
4.7%
a 418
 
4.7%
Other values (16) 2082
23.2%
Uppercase Letter
ValueCountFrequency (%)
S 139
30.1%
P 120
26.0%
X 43
 
9.3%
M 39
 
8.4%
K 30
 
6.5%
Q 17
 
3.7%
H 14
 
3.0%
A 10
 
2.2%
B 7
 
1.5%
L 5
 
1.1%
Other values (14) 38
 
8.2%
Decimal Number
ValueCountFrequency (%)
2 106
15.6%
0 101
14.9%
1 85
12.5%
5 80
11.8%
4 67
9.9%
3 64
9.4%
9 58
8.5%
6 46
6.8%
7 37
 
5.4%
8 36
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 877
52.7%
/ 656
39.4%
: 132
 
7.9%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9450
80.1%
Common 2353
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1323
14.0%
w 966
 
10.2%
s 725
 
7.7%
c 682
 
7.2%
h 658
 
7.0%
l 589
 
6.2%
t 570
 
6.0%
r 550
 
5.8%
g 425
 
4.5%
a 418
 
4.4%
Other values (40) 2544
26.9%
Common
ValueCountFrequency (%)
. 877
37.3%
/ 656
27.9%
: 132
 
5.6%
2 106
 
4.5%
0 101
 
4.3%
1 85
 
3.6%
5 80
 
3.4%
4 67
 
2.8%
3 64
 
2.7%
9 58
 
2.5%
Other values (4) 127
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11803
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1323
 
11.2%
w 966
 
8.2%
. 877
 
7.4%
s 725
 
6.1%
c 682
 
5.8%
h 658
 
5.6%
/ 656
 
5.6%
l 589
 
5.0%
t 570
 
4.8%
r 550
 
4.7%
Other values (54) 4207
35.6%
Distinct333
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size25.8 KiB
2023-12-09T22:18:27.850169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.128146453
Min length2

Characters and Unicode

Total characters1367
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)58.1%

Sample

1st row255
2nd row304
3rd row666
4th row363
5th row1735
ValueCountFrequency (%)
358 5
 
1.1%
479 4
 
0.9%
353 4
 
0.9%
428 4
 
0.9%
319 4
 
0.9%
587 3
 
0.7%
566 3
 
0.7%
438 3
 
0.7%
416 3
 
0.7%
471 3
 
0.7%
Other values (323) 401
91.8%
2023-12-09T22:18:28.493003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 201
14.7%
3 197
14.4%
2 149
10.9%
1 146
10.7%
5 145
10.6%
6 134
9.8%
7 109
8.0%
9 98
7.2%
8 96
7.0%
0 92
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1367
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 201
14.7%
3 197
14.4%
2 149
10.9%
1 146
10.7%
5 145
10.6%
6 134
9.8%
7 109
8.0%
9 98
7.2%
8 96
7.0%
0 92
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1367
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 201
14.7%
3 197
14.4%
2 149
10.9%
1 146
10.7%
5 145
10.6%
6 134
9.8%
7 109
8.0%
9 98
7.2%
8 96
7.0%
0 92
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 201
14.7%
3 197
14.4%
2 149
10.9%
1 146
10.7%
5 145
10.6%
6 134
9.8%
7 109
8.0%
9 98
7.2%
8 96
7.0%
0 92
6.7%

campus_name
Text

MISSING 

Distinct36
Distinct (%)28.3%
Missing310
Missing (%)70.9%
Memory size20.9 KiB
2023-12-09T22:18:28.818354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length36
Mean length32.78740157
Min length25

Characters and Unicode

Total characters4164
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rowPark West Educational Campus
2nd rowSeward Park Educational Campus
3rd rowPark West Educational Campus
4th rowPark West Educational Campus
5th rowPark West Educational Campus
ValueCountFrequency (%)
educational 127
24.2%
campus 126
24.0%
park 10
 
1.9%
john 7
 
1.3%
george 7
 
1.3%
evander 6
 
1.1%
theodore 6
 
1.1%
roosevelt 6
 
1.1%
childs 6
 
1.1%
monroe 5
 
1.0%
Other values (66) 219
41.7%
2023-12-09T22:18:29.308529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 520
 
12.5%
398
 
9.6%
u 285
 
6.8%
o 236
 
5.7%
n 227
 
5.5%
t 209
 
5.0%
s 207
 
5.0%
i 198
 
4.8%
l 190
 
4.6%
d 186
 
4.5%
Other values (33) 1508
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3219
77.3%
Uppercase Letter 524
 
12.6%
Space Separator 398
 
9.6%
Other Punctuation 23
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 520
16.2%
u 285
 
8.9%
o 236
 
7.3%
n 227
 
7.1%
t 209
 
6.5%
s 207
 
6.4%
i 198
 
6.2%
l 190
 
5.9%
d 186
 
5.8%
e 175
 
5.4%
Other values (13) 786
24.4%
Uppercase Letter
ValueCountFrequency (%)
E 146
27.9%
C 143
27.3%
J 31
 
5.9%
S 30
 
5.7%
H 26
 
5.0%
W 24
 
4.6%
T 18
 
3.4%
P 16
 
3.1%
M 16
 
3.1%
R 14
 
2.7%
Other values (7) 60
11.5%
Other Punctuation
ValueCountFrequency (%)
. 18
78.3%
, 5
 
21.7%
Space Separator
ValueCountFrequency (%)
398
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3743
89.9%
Common 421
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 520
 
13.9%
u 285
 
7.6%
o 236
 
6.3%
n 227
 
6.1%
t 209
 
5.6%
s 207
 
5.5%
i 198
 
5.3%
l 190
 
5.1%
d 186
 
5.0%
e 175
 
4.7%
Other values (30) 1310
35.0%
Common
ValueCountFrequency (%)
398
94.5%
. 18
 
4.3%
, 5
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 520
 
12.5%
398
 
9.6%
u 285
 
6.8%
o 236
 
5.7%
n 227
 
5.5%
t 209
 
5.0%
s 207
 
5.0%
i 198
 
4.8%
l 190
 
4.6%
d 186
 
4.5%
Other values (33) 1508
36.2%

school_type
Text

MISSING 

Distinct10
Distinct (%)8.9%
Missing325
Missing (%)74.4%
Memory size19.0 KiB
2023-12-09T22:18:29.505574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length66
Median length54
Mean length22.6875
Min length10

Characters and Unicode

Total characters2541
Distinct characters37
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st rowPerformance Assessment School
2nd rowCTE School
3rd rowCTE School
4th rowNYC P-Tech 9-14
5th rowCTE School
ValueCountFrequency (%)
school 122
33.3%
cte 40
 
10.9%
performance 38
 
10.4%
assessment 38
 
10.4%
for 22
 
6.0%
new 22
 
6.0%
arrivals 22
 
6.0%
all 13
 
3.6%
specialized 9
 
2.5%
high 9
 
2.5%
Other values (5) 31
 
8.5%
2023-12-09T22:18:29.833184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 308
12.1%
254
 
10.0%
e 198
 
7.8%
l 188
 
7.4%
s 187
 
7.4%
c 175
 
6.9%
r 151
 
5.9%
h 137
 
5.4%
S 131
 
5.2%
m 76
 
3.0%
Other values (27) 736
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1805
71.0%
Uppercase Letter 436
 
17.2%
Space Separator 254
 
10.0%
Decimal Number 18
 
0.7%
Other Punctuation 16
 
0.6%
Dash Punctuation 12
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 308
17.1%
e 198
11.0%
l 188
10.4%
s 187
10.4%
c 175
9.7%
r 151
8.4%
h 137
7.6%
m 76
 
4.2%
n 76
 
4.2%
a 69
 
3.8%
Other values (10) 240
13.3%
Uppercase Letter
ValueCountFrequency (%)
S 131
30.0%
A 73
16.7%
C 46
 
10.6%
T 46
 
10.6%
P 44
 
10.1%
E 40
 
9.2%
N 28
 
6.4%
H 9
 
2.1%
G 9
 
2.1%
Y 6
 
1.4%
Decimal Number
ValueCountFrequency (%)
9 6
33.3%
1 6
33.3%
4 6
33.3%
Space Separator
ValueCountFrequency (%)
254
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2241
88.2%
Common 300
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 308
13.7%
e 198
 
8.8%
l 188
 
8.4%
s 187
 
8.3%
c 175
 
7.8%
r 151
 
6.7%
h 137
 
6.1%
S 131
 
5.8%
m 76
 
3.4%
n 76
 
3.4%
Other values (21) 614
27.4%
Common
ValueCountFrequency (%)
254
84.7%
, 16
 
5.3%
- 12
 
4.0%
9 6
 
2.0%
1 6
 
2.0%
4 6
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 308
12.1%
254
 
10.0%
e 198
 
7.8%
l 188
 
7.4%
s 187
 
7.4%
c 175
 
6.9%
r 151
 
5.9%
h 137
 
5.4%
S 131
 
5.2%
m 76
 
3.0%
Other values (27) 736
29.0%

overview_paragraph
Text

UNIQUE 

Distinct437
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size407.7 KiB
2023-12-09T22:18:30.263955image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1491
Median length753
Mean length650.1510297
Min length122

Characters and Unicode

Total characters284116
Distinct characters85
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique437 ?
Unique (%)100.0%

Sample

1st rowHenry Street School for International Studies is a unique small school founded by the Asia Society. While in pursuit of knowledge about other world regions, including their histories, economies and world languages, students acquire the knowledge and skills needed to prepare for college and/or careers. Teachers and other adults who make up the learning community forge supportive relationships with students and parents while providing challenging and engaging learning experiences. Our school partners with various community, arts, and business organizations to help students achieve success. Our theme of international studies extends beyond the classroom, where students participate in ongoing ‘Advisory Day Out’ excursions where the multiculturalism of NYC becomes the classroom.
2nd rowUniversity Neighborhood High School (UNHS) is the first collaborative partnership school between New York University and the New York City Department of Education. We are proud to provide all kinds of learners with a challenging curriculum in a supportive environment so that they can successfully participate in higher education opportunities and the workforce.
3rd rowWe are a small secondary school that prepares all students for college and careers. We set high standards and work with all of our students to help them meet these standards. With no more than twenty-five students per class, teachers are able to provide personal attention in a respectful environment. Our staff makes sure that we know every student well. We assess our students by challenging them to use what they have learned in creative ways to complete interesting projects. Students, staff, families, and community members all see themselves as part of a team whose main goal is the success of every individual student.
4th rowMarta Valle High School (MVHS) offers a strong program of academic and character development in the tradition of our namesake Marta Valle, a social worker, youth advocate, and community organizer. Our Core Values – Respect, Leadership, Integrity, Diligence, and Service – are woven throughout everything we do. Our academics are supplemented by electives in the arts. Our students can earn college credit at the City University of New York (CUNY). MVHS is a place where ‘Educating Hearts and Minds for the 21st Century’ is a reality.
5th rowNew Explorations into Science, Technology and Math High School (NEST+m) is a K-12 school that is committed to providing an exemplary accelerated education for students of diverse backgrounds who have the ability and promise to meet the demands of an academically challenging curriculum. The Upper School (grades 9-12) engages students to think abstractly and critically, and encourages them to formulate questions that guide their learning experience via discussions and research. Multiple opportunities exist for students to have internships at local universities in the sciences and the arts.
ValueCountFrequency (%)
and 2415
 
5.8%
the 1480
 
3.5%
to 1445
 
3.4%
students 1162
 
2.8%
of 1096
 
2.6%
a 1034
 
2.5%
in 1004
 
2.4%
our 867
 
2.1%
school 689
 
1.6%
for 570
 
1.4%
Other values (3810) 30144
71.9%
2023-12-09T22:18:30.882779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41469
14.6%
e 27555
 
9.7%
t 18956
 
6.7%
a 17939
 
6.3%
n 17698
 
6.2%
o 17132
 
6.0%
i 17062
 
6.0%
r 15882
 
5.6%
s 15859
 
5.6%
l 11369
 
4.0%
Other values (75) 83195
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 229017
80.6%
Space Separator 41469
 
14.6%
Uppercase Letter 7096
 
2.5%
Other Punctuation 4806
 
1.7%
Dash Punctuation 765
 
0.3%
Decimal Number 273
 
0.1%
Close Punctuation 229
 
0.1%
Open Punctuation 229
 
0.1%
Final Punctuation 190
 
0.1%
Initial Punctuation 40
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 27555
12.0%
t 18956
 
8.3%
a 17939
 
7.8%
n 17698
 
7.7%
o 17132
 
7.5%
i 17062
 
7.5%
r 15882
 
6.9%
s 15859
 
6.9%
l 11369
 
5.0%
c 10395
 
4.5%
Other values (18) 59170
25.8%
Uppercase Letter
ValueCountFrequency (%)
S 928
13.1%
A 742
 
10.5%
C 702
 
9.9%
T 557
 
7.8%
W 466
 
6.6%
E 449
 
6.3%
O 417
 
5.9%
H 330
 
4.7%
L 286
 
4.0%
P 273
 
3.8%
Other values (15) 1946
27.4%
Other Punctuation
ValueCountFrequency (%)
, 2623
54.6%
. 2003
41.7%
/ 45
 
0.9%
: 44
 
0.9%
' 33
 
0.7%
; 22
 
0.5%
& 16
 
0.3%
! 9
 
0.2%
? 8
 
0.2%
% 3
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 69
25.3%
0 67
24.5%
2 60
22.0%
9 18
 
6.6%
5 16
 
5.9%
6 15
 
5.5%
4 13
 
4.8%
3 9
 
3.3%
8 4
 
1.5%
7 2
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 723
94.5%
29
 
3.8%
13
 
1.7%
Final Punctuation
ValueCountFrequency (%)
168
88.4%
22
 
11.6%
Initial Punctuation
ValueCountFrequency (%)
22
55.0%
18
45.0%
Space Separator
ValueCountFrequency (%)
41469
100.0%
Close Punctuation
ValueCountFrequency (%)
) 229
100.0%
Open Punctuation
ValueCountFrequency (%)
( 229
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 236113
83.1%
Common 48003
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 27555
11.7%
t 18956
 
8.0%
a 17939
 
7.6%
n 17698
 
7.5%
o 17132
 
7.3%
i 17062
 
7.2%
r 15882
 
6.7%
s 15859
 
6.7%
l 11369
 
4.8%
c 10395
 
4.4%
Other values (43) 66266
28.1%
Common
ValueCountFrequency (%)
41469
86.4%
, 2623
 
5.5%
. 2003
 
4.2%
- 723
 
1.5%
) 229
 
0.5%
( 229
 
0.5%
168
 
0.3%
1 69
 
0.1%
0 67
 
0.1%
2 60
 
0.1%
Other values (22) 363
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 283841
99.9%
Punctuation 272
 
0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41469
14.6%
e 27555
 
9.7%
t 18956
 
6.7%
a 17939
 
6.3%
n 17698
 
6.2%
o 17132
 
6.0%
i 17062
 
6.0%
r 15882
 
5.6%
s 15859
 
5.6%
l 11369
 
4.0%
Other values (67) 82920
29.2%
Punctuation
ValueCountFrequency (%)
168
61.8%
29
 
10.7%
22
 
8.1%
22
 
8.1%
18
 
6.6%
13
 
4.8%
None
ValueCountFrequency (%)
é 2
66.7%
ó 1
33.3%
Distinct436
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size216.9 KiB
2023-12-09T22:18:31.237060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1356
Median length464.5
Mean length385.0229358
Min length13

Characters and Unicode

Total characters167870
Distinct characters84
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique436 ?
Unique (%)100.0%

Sample

1st rowGlobal/International Studies in core subjects; Literacy block schedule; Personalized instruction in small classes; Student Advisories; International travel opportunities; After-school program focused on youth leadership
2nd rowUNHS students can earn up to 24 tuition-free college credits by taking CUNY College Now classes at the Baruch College Campus or at UNHS during the regular school day in addition to taking courses at LaGuardia College, BMCC or St. John’s University; courses include Business, Speech Communication, Psychology, and Personal Finance. Variety of innovative technology courses such as Microsoft Office Suite, Computer Programming, Computer Coding, Gaming, Web Design, Adobe Suite, and Film Production. Two Sigma, one of our technology partnerships, is currently open to ninth and tenth graders to develop in-depth computer technology skills. Other academic opportunities include College Summit, Kaplan SAT prep review classes, Saturday Regents Prep, Saturday ESL classes at St. John’s University, an Advanced Regents Diploma honors program, and the Deloitte Academy mentoring program.
3rd rowOur advisory system ensures that we can effectively address our students’ and their families’ needs; Through the College Bound Initiative, our full-time college counselor helps prepare students for the college application process; Advanced students take CUNY College Now at Hunter College; Electives include Visual Art, Rapping/Poetry & Beat Making, Choir, Digital Art and Photography, Skateboarding, Film Making, Chess, Dance, Bicycling, and Video Game Design
4th rowAdvanced Regents Diploma; CUNY College Now; Mastery-based Grading System; Advisory program; College Placement Office and College Advisor; Statistics, Culinary Arts, Video and Music Production, Piano, Visual Art, Drama, Dance, Advisory, Fitness and Weight Training Studio, Technology Integration through Blended Online Instructional Model; Media, Living Environment, and Chemistry Science Labs
5th rowFirst Level Science Sequence: Ninth grade Regents Physics with a Recitation/Applications course; Tenth grade Regents Chemistry and one term of Computer Science with the option of an Student Research class; Eleventh grade Living Environment; Twelfth grade options include science electives and Advanced Placement (AP) courses; Second level science sequence is for accelerated students who have demonstrated aptitude for the sciences and mathematics; can begin AP courses in ninth, tenth, and eleventh grades.
ValueCountFrequency (%)
and 1043
 
4.7%
college 790
 
3.6%
in 434
 
2.0%
program 337
 
1.5%
the 331
 
1.5%
of 328
 
1.5%
students 288
 
1.3%
to 270
 
1.2%
courses 240
 
1.1%
cuny 238
 
1.1%
Other values (3025) 17861
80.6%
2023-12-09T22:18:31.776895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21724
 
12.9%
e 15180
 
9.0%
n 10169
 
6.1%
r 10134
 
6.0%
i 10045
 
6.0%
o 9926
 
5.9%
a 9613
 
5.7%
t 9186
 
5.5%
s 8404
 
5.0%
l 6367
 
3.8%
Other values (74) 57122
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 124390
74.1%
Space Separator 21724
 
12.9%
Uppercase Letter 14907
 
8.9%
Other Punctuation 5410
 
3.2%
Dash Punctuation 520
 
0.3%
Open Punctuation 335
 
0.2%
Close Punctuation 335
 
0.2%
Decimal Number 163
 
0.1%
Final Punctuation 62
 
< 0.1%
Math Symbol 15
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15180
12.2%
n 10169
 
8.2%
r 10134
 
8.1%
i 10045
 
8.1%
o 9926
 
8.0%
a 9613
 
7.7%
t 9186
 
7.4%
s 8404
 
6.8%
l 6367
 
5.1%
c 5415
 
4.4%
Other values (18) 29951
24.1%
Uppercase Letter
ValueCountFrequency (%)
C 2247
15.1%
S 1543
 
10.4%
A 1533
 
10.3%
P 1226
 
8.2%
T 922
 
6.2%
E 809
 
5.4%
N 777
 
5.2%
M 663
 
4.4%
I 571
 
3.8%
L 488
 
3.3%
Other values (16) 4128
27.7%
Decimal Number
ValueCountFrequency (%)
1 47
28.8%
0 37
22.7%
2 25
15.3%
3 13
 
8.0%
9 11
 
6.7%
5 10
 
6.1%
4 9
 
5.5%
8 5
 
3.1%
6 4
 
2.5%
7 2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 3721
68.8%
; 935
 
17.3%
. 316
 
5.8%
: 170
 
3.1%
/ 128
 
2.4%
& 127
 
2.3%
' 9
 
0.2%
@ 2
 
< 0.1%
! 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 517
99.4%
3
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 334
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 334
99.7%
] 1
 
0.3%
Space Separator
ValueCountFrequency (%)
21724
100.0%
Final Punctuation
ValueCountFrequency (%)
62
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Initial Punctuation
ValueCountFrequency (%)
8
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 139297
83.0%
Common 28573
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15180
 
10.9%
n 10169
 
7.3%
r 10134
 
7.3%
i 10045
 
7.2%
o 9926
 
7.1%
a 9613
 
6.9%
t 9186
 
6.6%
s 8404
 
6.0%
l 6367
 
4.6%
c 5415
 
3.9%
Other values (44) 44858
32.2%
Common
ValueCountFrequency (%)
21724
76.0%
, 3721
 
13.0%
; 935
 
3.3%
- 517
 
1.8%
( 334
 
1.2%
) 334
 
1.2%
. 316
 
1.1%
: 170
 
0.6%
/ 128
 
0.4%
& 127
 
0.4%
Other values (20) 267
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 167791
> 99.9%
Punctuation 73
 
< 0.1%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21724
 
12.9%
e 15180
 
9.0%
n 10169
 
6.1%
r 10134
 
6.0%
i 10045
 
6.0%
o 9926
 
5.9%
a 9613
 
5.7%
t 9186
 
5.5%
s 8404
 
5.0%
l 6367
 
3.8%
Other values (68) 57043
34.0%
Punctuation
ValueCountFrequency (%)
62
84.9%
8
 
11.0%
3
 
4.1%
None
ValueCountFrequency (%)
ñ 3
50.0%
é 2
33.3%
® 1
 
16.7%

language_classes
Text

MISSING 

Distinct69
Distinct (%)16.8%
Missing27
Missing (%)6.2%
Memory size30.4 KiB
2023-12-09T22:18:31.986354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length121
Median length7
Mean length16.58780488
Min length6

Characters and Unicode

Total characters6801
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)12.7%

Sample

1st rowChinese (Mandarin), Spanish
2nd rowChinese (Mandarin), Spanish
3rd rowFrench, Spanish
4th rowFrench, Spanish
5th rowChinese (Mandarin), French, Italian, Latin, Spanish
ValueCountFrequency (%)
spanish 387
44.8%
french 133
 
15.4%
italian 55
 
6.4%
chinese 53
 
6.1%
mandarin 46
 
5.3%
american 24
 
2.8%
sign 24
 
2.8%
language 24
 
2.8%
latin 24
 
2.8%
japanese 24
 
2.8%
Other values (16) 70
 
8.1%
2023-12-09T22:18:32.369607image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 889
13.1%
a 786
11.6%
i 648
9.5%
h 574
8.4%
s 494
 
7.3%
454
 
6.7%
p 411
 
6.0%
S 411
 
6.0%
e 403
 
5.9%
, 354
 
5.2%
Other values (32) 1377
20.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5021
73.8%
Uppercase Letter 866
 
12.7%
Space Separator 454
 
6.7%
Other Punctuation 354
 
5.2%
Open Punctuation 52
 
0.8%
Close Punctuation 52
 
0.8%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 889
17.7%
a 786
15.7%
i 648
12.9%
h 574
11.4%
s 494
9.8%
p 411
8.2%
e 403
8.0%
r 248
 
4.9%
c 167
 
3.3%
t 91
 
1.8%
Other values (10) 310
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 411
47.5%
F 133
 
15.4%
C 61
 
7.0%
I 55
 
6.4%
L 48
 
5.5%
M 46
 
5.3%
A 34
 
3.9%
J 24
 
2.8%
G 19
 
2.2%
R 10
 
1.2%
Other values (7) 25
 
2.9%
Space Separator
ValueCountFrequency (%)
454
100.0%
Other Punctuation
ValueCountFrequency (%)
, 354
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5887
86.6%
Common 914
 
13.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 889
15.1%
a 786
13.4%
i 648
11.0%
h 574
9.8%
s 494
8.4%
p 411
7.0%
S 411
7.0%
e 403
6.8%
r 248
 
4.2%
c 167
 
2.8%
Other values (27) 856
14.5%
Common
ValueCountFrequency (%)
454
49.7%
, 354
38.7%
( 52
 
5.7%
) 52
 
5.7%
- 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 889
13.1%
a 786
11.6%
i 648
9.5%
h 574
8.4%
s 494
 
7.3%
454
 
6.7%
p 411
 
6.0%
S 411
 
6.0%
e 403
 
5.9%
, 354
 
5.2%
Other values (32) 1377
20.2%
Distinct227
Distinct (%)72.5%
Missing124
Missing (%)28.4%
Memory size42.0 KiB
2023-12-09T22:18:32.605824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length358
Median length159
Mean length67.15654952
Min length7

Characters and Unicode

Total characters21020
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique190 ?
Unique (%)60.7%

Sample

1st rowChinese Language and Culture, Psychology, United States History
2nd rowCalculus, Chinese Language and Culture, English, Spanish, Studio Art, United States Government and Politics, World History
3rd rowEnglish
4th rowCalculus, Chemistry, Chinese Language and Culture, Computer Science A, Economics, English, European History, Human Geography, Latin, Physics, Spanish, United States History, World History
5th rowEnglish
ValueCountFrequency (%)
history 289
 
11.4%
english 255
 
10.1%
united 245
 
9.7%
states 245
 
9.7%
calculus 144
 
5.7%
biology 129
 
5.1%
and 123
 
4.9%
spanish 108
 
4.3%
science 92
 
3.6%
world 82
 
3.2%
Other values (26) 814
32.2%
2023-12-09T22:18:33.036691image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2213
 
10.5%
i 1688
 
8.0%
t 1665
 
7.9%
s 1516
 
7.2%
n 1363
 
6.5%
e 1184
 
5.6%
, 1143
 
5.4%
o 1113
 
5.3%
l 1007
 
4.8%
a 943
 
4.5%
Other values (26) 7185
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15261
72.6%
Uppercase Letter 2403
 
11.4%
Space Separator 2213
 
10.5%
Other Punctuation 1143
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1688
11.1%
t 1665
10.9%
s 1516
9.9%
n 1363
8.9%
e 1184
 
7.8%
o 1113
 
7.3%
l 1007
 
6.6%
a 943
 
6.2%
r 750
 
4.9%
c 665
 
4.4%
Other values (8) 3367
22.1%
Uppercase Letter
ValueCountFrequency (%)
S 544
22.6%
E 377
15.7%
H 304
12.7%
C 293
12.2%
U 245
10.2%
P 165
 
6.9%
B 129
 
5.4%
G 88
 
3.7%
W 82
 
3.4%
A 65
 
2.7%
Other values (6) 111
 
4.6%
Space Separator
ValueCountFrequency (%)
2213
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17664
84.0%
Common 3356
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1688
 
9.6%
t 1665
 
9.4%
s 1516
 
8.6%
n 1363
 
7.7%
e 1184
 
6.7%
o 1113
 
6.3%
l 1007
 
5.7%
a 943
 
5.3%
r 750
 
4.2%
c 665
 
3.8%
Other values (24) 5770
32.7%
Common
ValueCountFrequency (%)
2213
65.9%
, 1143
34.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2213
 
10.5%
i 1688
 
8.0%
t 1665
 
7.9%
s 1516
 
7.2%
n 1363
 
6.5%
e 1184
 
5.6%
, 1143
 
5.4%
o 1113
 
5.3%
l 1007
 
4.8%
a 943
 
4.5%
Other values (26) 7185
34.2%

diplomaendorsements
Text

MISSING 

Distinct11
Distinct (%)10.5%
Missing332
Missing (%)76.0%
Memory size17.3 KiB
2023-12-09T22:18:33.214272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length24
Median length19
Mean length8.99047619
Min length3

Characters and Unicode

Total characters944
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st rowScience
2nd rowMath, Science
3rd rowCTE
4th rowArts
5th rowCTE
ValueCountFrequency (%)
math 53
30.6%
science 53
30.6%
cte 43
24.9%
arts 24
13.9%
2023-12-09T22:18:33.500382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 106
11.2%
c 106
11.2%
t 77
 
8.2%
, 68
 
7.2%
68
 
7.2%
M 53
 
5.6%
a 53
 
5.6%
n 53
 
5.6%
i 53
 
5.6%
S 53
 
5.6%
Other values (7) 254
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 549
58.2%
Uppercase Letter 259
27.4%
Other Punctuation 68
 
7.2%
Space Separator 68
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 106
19.3%
c 106
19.3%
t 77
14.0%
a 53
9.7%
n 53
9.7%
i 53
9.7%
h 53
9.7%
r 24
 
4.4%
s 24
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
M 53
20.5%
S 53
20.5%
C 43
16.6%
T 43
16.6%
E 43
16.6%
A 24
9.3%
Other Punctuation
ValueCountFrequency (%)
, 68
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 808
85.6%
Common 136
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 106
13.1%
c 106
13.1%
t 77
9.5%
M 53
 
6.6%
a 53
 
6.6%
n 53
 
6.6%
i 53
 
6.6%
S 53
 
6.6%
h 53
 
6.6%
C 43
 
5.3%
Other values (5) 158
19.6%
Common
ValueCountFrequency (%)
, 68
50.0%
68
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 106
11.2%
c 106
11.2%
t 77
 
8.2%
, 68
 
7.2%
68
 
7.2%
M 53
 
5.6%
a 53
 
5.6%
n 53
 
5.6%
i 53
 
5.6%
S 53
 
5.6%
Other values (7) 254
26.9%
Distinct435
Distinct (%)99.8%
Missing1
Missing (%)0.2%
Memory size192.2 KiB
2023-12-09T22:18:33.852897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1062
Median length409.5
Mean length318.3417431
Min length23

Characters and Unicode

Total characters138797
Distinct characters82
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique434 ?
Unique (%)99.5%

Sample

1st rowMath through Card Play; Art, Poetry/Spoken Word, Drama, Book, STEP, Big Brothers/Big Sisters, Student Government/Leadership, Future Project
2nd rowBasketball, Badminton, Handball, Glee, Dance (in our state-of-the-art dance studio), Weight Training (in our newly-renovated gym), Ping Pong, Tennis, Step Team, After-School Tutoring, Peer Tutoring, Lunchtime Tutoring, Saturday SAT Prep, Saturday Regents Prep, ESL Saturday Academy, Regents Prep, National Honor Society, Council for Unity, Young Women’s Empowerment, Student Assistance Services, Aviation, Book, Chess, Robotics, Computer, Spanish, Student Government, Art, Audio (at a live radio station), Music, Digital Art Studio, Guitar and Piano, Literary Magazine, Murals and School Beautification, Video and Cooking. At UNHS, we will also help any student develop any club that has 10 or more students interested in joining.
3rd rowAfter-School Tutoring, Art Portfolio Classes, Chess Team, I Challenge Myself Bicycling Program, Dance, Environmental Committee, Gay/Straight Alliance, Hip-Hop Beat Making & Rhyming, Model UN, School Newspaper, Peer Tutoring, the Brotherhood and Girl’s Group, Principal’s Book Club, Yoga, Rock Band Program, SAT Prep Classes, Scholars Program, School Newspaper, Skateboarding PE Classes, Student Council, Cheerleading, Gardening Internships, Choir, Travel, Volleyball, Morgan Stanley Internship Program, Saturday Photography Program, Rock Climbing at Brooklyn Boulders, Golf, Video Game Design, Surfing and Snowboarding through Stoked
4th rowModel Peer Leadership Program, ‘The Vine’ Student Newsletter, After-school Program, Student Ambassadors, Animation, College and Career Fair, Family Night, Art, Audio Recording, Camping, Cheerleading, Chorus, Dance, Film, Gallatin Great Works Project (NYU), Kaplan SAT Prep, Monthly Family Resource Fairs, MOUSE Squad, National Honor Society, Painting, Peer Mediation and Conflict Resolution, Princeton Center for Leadership, Recycling, Fashion Show, Songwriting, Step, Student Advisory Council, Sarah Lawrence College Student Interns, Lunchtime Cafe Clubs, Theater, Voice, Young Entrepreneurs
5th rowAfter-School Jazz Band, Annual Coffee House Concert, Annual Gallery Walk Art Exhibitions, Borough Advisory Student Council, Community Service Learning, Competitive Ballroom Dancing, Creative Writing, Debate Committee, Debate Team, Educational Field Trips, Green Club, Gay-Straight Alliance (GSA), Handball, Heart to Heart Charity, Kangaroo International Competition, Mandarin, Math Team, Model UN, National and Local Chess Championships, National Honor Society, Annual Talent Show, New York Math League Competition, Peer Leaders, Red Cross, Robotics, Scholastic Arts Competition, School Leadership Team (SLT), Social Justice, Student Government, Chorus, The Gauss Contest, The Purple Meet, Ultimate Frisbee, Winter and Spring School Plays, World Science Festival
ValueCountFrequency (%)
student 489
 
2.8%
and 410
 
2.3%
team 290
 
1.6%
dance 284
 
1.6%
club 267
 
1.5%
government 255
 
1.4%
society 254
 
1.4%
peer 227
 
1.3%
honor 221
 
1.3%
art 219
 
1.2%
Other values (2612) 14699
83.4%
2023-12-09T22:18:34.405493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17179
 
12.4%
e 11445
 
8.2%
o 8457
 
6.1%
a 8222
 
5.9%
n 7984
 
5.8%
t 7953
 
5.7%
r 7945
 
5.7%
i 7705
 
5.6%
, 7337
 
5.3%
s 4976
 
3.6%
Other values (72) 49594
35.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 94773
68.3%
Uppercase Letter 17884
 
12.9%
Space Separator 17179
 
12.4%
Other Punctuation 7916
 
5.7%
Dash Punctuation 319
 
0.2%
Close Punctuation 271
 
0.2%
Open Punctuation 271
 
0.2%
Final Punctuation 96
 
0.1%
Decimal Number 70
 
0.1%
Initial Punctuation 15
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11445
12.1%
o 8457
 
8.9%
a 8222
 
8.7%
n 7984
 
8.4%
t 7953
 
8.4%
r 7945
 
8.4%
i 7705
 
8.1%
s 4976
 
5.3%
l 4245
 
4.5%
c 3672
 
3.9%
Other values (17) 22169
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 2606
14.6%
C 2072
11.6%
A 1587
 
8.9%
T 1314
 
7.3%
P 1289
 
7.2%
M 1171
 
6.5%
D 953
 
5.3%
G 802
 
4.5%
N 634
 
3.5%
H 627
 
3.5%
Other values (16) 4829
27.0%
Other Punctuation
ValueCountFrequency (%)
, 7337
92.7%
; 184
 
2.3%
/ 164
 
2.1%
& 71
 
0.9%
. 58
 
0.7%
' 51
 
0.6%
: 43
 
0.5%
! 6
 
0.1%
? 1
 
< 0.1%
¡ 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 16
22.9%
0 13
18.6%
1 11
15.7%
4 9
12.9%
3 9
12.9%
5 4
 
5.7%
9 4
 
5.7%
8 3
 
4.3%
6 1
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 318
99.7%
1
 
0.3%
Final Punctuation
ValueCountFrequency (%)
94
97.9%
2
 
2.1%
Initial Punctuation
ValueCountFrequency (%)
13
86.7%
2
 
13.3%
Space Separator
ValueCountFrequency (%)
17179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 271
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 112657
81.2%
Common 26140
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11445
 
10.2%
o 8457
 
7.5%
a 8222
 
7.3%
n 7984
 
7.1%
t 7953
 
7.1%
r 7945
 
7.1%
i 7705
 
6.8%
s 4976
 
4.4%
l 4245
 
3.8%
c 3672
 
3.3%
Other values (43) 40053
35.6%
Common
ValueCountFrequency (%)
17179
65.7%
, 7337
28.1%
- 318
 
1.2%
) 271
 
1.0%
( 271
 
1.0%
; 184
 
0.7%
/ 164
 
0.6%
94
 
0.4%
& 71
 
0.3%
. 58
 
0.2%
Other values (19) 193
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138683
99.9%
Punctuation 112
 
0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17179
 
12.4%
e 11445
 
8.3%
o 8457
 
6.1%
a 8222
 
5.9%
n 7984
 
5.8%
t 7953
 
5.7%
r 7945
 
5.7%
i 7705
 
5.6%
, 7337
 
5.3%
s 4976
 
3.6%
Other values (65) 49480
35.7%
Punctuation
ValueCountFrequency (%)
94
83.9%
13
 
11.6%
2
 
1.8%
2
 
1.8%
1
 
0.9%
None
ValueCountFrequency (%)
¡ 1
50.0%
ñ 1
50.0%

psal_sports_boys
Text

MISSING 

Distinct151
Distinct (%)38.2%
Missing42
Missing (%)9.6%
Memory size49.8 KiB
2023-12-09T22:18:34.628443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length198
Median length116
Mean length68.33417722
Min length6

Characters and Unicode

Total characters26992
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)19.2%

Sample

1st rowBasketball
2nd rowBasketball, Bowling, Handball
3rd rowBaseball, Basketball, Soccer
4th rowBasketball
5th rowBasketball, Fencing, Indoor Track, Soccer
ValueCountFrequency (%)
basketball 386
12.8%
track 336
11.2%
baseball 309
10.3%
soccer 286
9.5%
volleyball 196
 
6.5%
outdoor 182
 
6.1%
bowling 166
 
5.5%
wrestling 156
 
5.2%
indoor 154
 
5.1%
country 133
 
4.4%
Other values (11) 700
23.3%
2023-12-09T22:18:35.044846image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2972
 
11.0%
2609
 
9.7%
a 2350
 
8.7%
, 2124
 
7.9%
o 1908
 
7.1%
e 1538
 
5.7%
r 1417
 
5.2%
s 1341
 
5.0%
b 1157
 
4.3%
n 1156
 
4.3%
Other values (23) 8420
31.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19255
71.3%
Uppercase Letter 3004
 
11.1%
Space Separator 2609
 
9.7%
Other Punctuation 2124
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 2972
15.4%
a 2350
12.2%
o 1908
9.9%
e 1538
8.0%
r 1417
7.4%
s 1341
 
7.0%
b 1157
 
6.0%
n 1156
 
6.0%
t 1028
 
5.3%
c 989
 
5.1%
Other values (8) 3399
17.7%
Uppercase Letter
ValueCountFrequency (%)
B 890
29.6%
T 474
15.8%
S 355
 
11.8%
C 266
 
8.9%
V 196
 
6.5%
O 182
 
6.1%
F 158
 
5.3%
W 156
 
5.2%
I 154
 
5.1%
H 102
 
3.4%
Other values (3) 71
 
2.4%
Space Separator
ValueCountFrequency (%)
2609
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22259
82.5%
Common 4733
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 2972
13.4%
a 2350
 
10.6%
o 1908
 
8.6%
e 1538
 
6.9%
r 1417
 
6.4%
s 1341
 
6.0%
b 1157
 
5.2%
n 1156
 
5.2%
t 1028
 
4.6%
c 989
 
4.4%
Other values (21) 6403
28.8%
Common
ValueCountFrequency (%)
2609
55.1%
, 2124
44.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26992
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 2972
 
11.0%
2609
 
9.7%
a 2350
 
8.7%
, 2124
 
7.9%
o 1908
 
7.1%
e 1538
 
5.7%
r 1417
 
5.2%
s 1341
 
5.0%
b 1157
 
4.3%
n 1156
 
4.3%
Other values (23) 8420
31.2%

psal_sports_girls
Text

MISSING 

Distinct157
Distinct (%)40.7%
Missing51
Missing (%)11.7%
Memory size47.8 KiB
2023-12-09T22:18:35.270541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length209
Median length134
Mean length65.35233161
Min length8

Characters and Unicode

Total characters25226
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)21.8%

Sample

1st rowBowling, Softball
2nd rowBasketball, Soccer, Softball, Volleyball
3rd rowBadminton
4th rowBasketball, Fencing, Soccer, Softball, Volleyball
5th rowBasketball, Cross Country, Outdoor Track, Soccer, Tennis, Volleyball
ValueCountFrequency (%)
basketball 343
12.0%
volleyball 314
11.0%
track 299
10.5%
softball 284
9.9%
soccer 192
 
6.7%
tennis 172
 
6.0%
outdoor 152
 
5.3%
indoor 147
 
5.1%
cross 132
 
4.6%
country 132
 
4.6%
Other values (14) 688
24.1%
2023-12-09T22:18:35.689507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3171
 
12.6%
2469
 
9.8%
o 2068
 
8.2%
a 2042
 
8.1%
, 1916
 
7.6%
b 1155
 
4.6%
e 1137
 
4.5%
t 1134
 
4.5%
r 1132
 
4.5%
n 1038
 
4.1%
Other values (24) 7964
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17986
71.3%
Uppercase Letter 2855
 
11.3%
Space Separator 2469
 
9.8%
Other Punctuation 1916
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 3171
17.6%
o 2068
11.5%
a 2042
11.4%
b 1155
 
6.4%
e 1137
 
6.3%
t 1134
 
6.3%
r 1132
 
6.3%
n 1038
 
5.8%
s 953
 
5.3%
c 769
 
4.3%
Other values (9) 3387
18.8%
Uppercase Letter
ValueCountFrequency (%)
S 549
19.2%
T 490
17.2%
B 483
16.9%
V 314
11.0%
C 264
9.2%
F 225
7.9%
O 152
 
5.3%
I 147
 
5.1%
H 72
 
2.5%
G 61
 
2.1%
Other values (3) 98
 
3.4%
Space Separator
ValueCountFrequency (%)
2469
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20841
82.6%
Common 4385
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 3171
15.2%
o 2068
 
9.9%
a 2042
 
9.8%
b 1155
 
5.5%
e 1137
 
5.5%
t 1134
 
5.4%
r 1132
 
5.4%
n 1038
 
5.0%
s 953
 
4.6%
c 769
 
3.7%
Other values (22) 6242
30.0%
Common
ValueCountFrequency (%)
2469
56.3%
, 1916
43.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 3171
 
12.6%
2469
 
9.8%
o 2068
 
8.2%
a 2042
 
8.1%
, 1916
 
7.6%
b 1155
 
4.6%
e 1137
 
4.5%
t 1134
 
4.5%
r 1132
 
4.5%
n 1038
 
4.1%
Other values (24) 7964
31.6%

psal_sports_coed
Text

MISSING 

Distinct15
Distinct (%)11.2%
Missing303
Missing (%)69.3%
Memory size18.4 KiB
2023-12-09T22:18:35.882487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length46
Median length22
Mean length9.970149254
Min length4

Characters and Unicode

Total characters1336
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.0%

Sample

1st rowTable Tennis
2nd rowBowling, Cross Country, Handball, Indoor Track
3rd rowWrestling
4th rowGolf
5th rowGolf
ValueCountFrequency (%)
cricket 61
28.1%
golf 53
24.4%
double 35
16.1%
dutch 35
16.1%
stunt 16
 
7.4%
table 4
 
1.8%
tennis 4
 
1.8%
softball 2
 
0.9%
wrestling 1
 
0.5%
bowling 1
 
0.5%
Other values (5) 5
 
2.3%
2023-12-09T22:18:36.214613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 132
 
9.9%
e 105
 
7.9%
l 100
 
7.5%
c 97
 
7.3%
o 95
 
7.1%
u 87
 
6.5%
83
 
6.2%
D 70
 
5.2%
i 67
 
5.0%
r 66
 
4.9%
Other values (20) 434
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 994
74.4%
Uppercase Letter 217
 
16.2%
Space Separator 83
 
6.2%
Other Punctuation 42
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 132
13.3%
e 105
10.6%
l 100
10.1%
c 97
9.8%
o 95
9.6%
u 87
8.8%
i 67
6.7%
r 66
6.6%
k 62
6.2%
f 55
5.5%
Other values (9) 128
12.9%
Uppercase Letter
ValueCountFrequency (%)
D 70
32.3%
C 63
29.0%
G 53
24.4%
S 18
 
8.3%
T 9
 
4.1%
W 1
 
0.5%
B 1
 
0.5%
H 1
 
0.5%
I 1
 
0.5%
Space Separator
ValueCountFrequency (%)
83
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1211
90.6%
Common 125
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 132
10.9%
e 105
 
8.7%
l 100
 
8.3%
c 97
 
8.0%
o 95
 
7.8%
u 87
 
7.2%
D 70
 
5.8%
i 67
 
5.5%
r 66
 
5.5%
C 63
 
5.2%
Other values (18) 329
27.2%
Common
ValueCountFrequency (%)
83
66.4%
, 42
33.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 132
 
9.9%
e 105
 
7.9%
l 100
 
7.5%
c 97
 
7.3%
o 95
 
7.1%
u 87
 
6.5%
83
 
6.2%
D 70
 
5.2%
i 67
 
5.0%
r 66
 
4.9%
Other values (20) 434
32.5%

school_sports
Text

MISSING 

Distinct280
Distinct (%)94.0%
Missing139
Missing (%)31.8%
Memory size39.7 KiB
2023-12-09T22:18:36.595511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length505
Median length112
Mean length61.81879195
Min length6

Characters and Unicode

Total characters18422
Distinct characters74
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)91.9%

Sample

1st rowBoxing, Track, CHAMPS, Tennis, Flag Football, Softball
2nd rowBasketball, Bicycling, Fitness, Indoor Soccer, Skateboarding, Softball, Volleyball, Rock Climbing, Snowboarding, Surfing
3rd rowVolleyball, Zumba
4th rowBadminton, Baseball, Cross-Country, Dance, Outdoor Track, Soccer, Softball, Table Tennis, Volleyball
5th rowCo-ed Ultimate Frisbee
ValueCountFrequency (%)
basketball 158
 
6.7%
soccer 93
 
4.0%
volleyball 86
 
3.7%
football 74
 
3.2%
cheerleading 70
 
3.0%
intramural 66
 
2.8%
track 64
 
2.7%
baseball 61
 
2.6%
flag 60
 
2.6%
and 57
 
2.4%
Other values (388) 1557
66.4%
2023-12-09T22:18:37.172087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2048
 
11.1%
l 1649
 
9.0%
a 1534
 
8.3%
e 1344
 
7.3%
o 989
 
5.4%
t 921
 
5.0%
r 857
 
4.7%
n 824
 
4.5%
s 809
 
4.4%
, 795
 
4.3%
Other values (64) 6652
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13255
72.0%
Uppercase Letter 2072
 
11.2%
Space Separator 2048
 
11.1%
Other Punctuation 920
 
5.0%
Dash Punctuation 49
 
0.3%
Final Punctuation 25
 
0.1%
Decimal Number 22
 
0.1%
Open Punctuation 15
 
0.1%
Close Punctuation 15
 
0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1649
12.4%
a 1534
11.6%
e 1344
10.1%
o 989
 
7.5%
t 921
 
6.9%
r 857
 
6.5%
n 824
 
6.2%
s 809
 
6.1%
i 762
 
5.7%
b 556
 
4.2%
Other values (16) 3010
22.7%
Uppercase Letter
ValueCountFrequency (%)
B 324
15.6%
S 309
14.9%
F 213
10.3%
C 211
10.2%
T 195
9.4%
V 113
 
5.5%
I 85
 
4.1%
G 84
 
4.1%
A 70
 
3.4%
W 62
 
3.0%
Other values (15) 406
19.6%
Other Punctuation
ValueCountFrequency (%)
, 795
86.4%
. 38
 
4.1%
: 34
 
3.7%
; 28
 
3.0%
& 12
 
1.3%
' 6
 
0.7%
/ 5
 
0.5%
! 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 4
18.2%
1 4
18.2%
9 3
13.6%
0 3
13.6%
7 3
13.6%
3 2
9.1%
8 2
9.1%
5 1
 
4.5%
Final Punctuation
ValueCountFrequency (%)
24
96.0%
1
 
4.0%
Space Separator
ValueCountFrequency (%)
2048
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15327
83.2%
Common 3095
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1649
 
10.8%
a 1534
 
10.0%
e 1344
 
8.8%
o 989
 
6.5%
t 921
 
6.0%
r 857
 
5.6%
n 824
 
5.4%
s 809
 
5.3%
i 762
 
5.0%
b 556
 
3.6%
Other values (41) 5082
33.2%
Common
ValueCountFrequency (%)
2048
66.2%
, 795
 
25.7%
- 49
 
1.6%
. 38
 
1.2%
: 34
 
1.1%
; 28
 
0.9%
24
 
0.8%
( 15
 
0.5%
) 15
 
0.5%
& 12
 
0.4%
Other values (13) 37
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18396
99.9%
Punctuation 26
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2048
 
11.1%
l 1649
 
9.0%
a 1534
 
8.3%
e 1344
 
7.3%
o 989
 
5.4%
t 921
 
5.0%
r 857
 
4.7%
n 824
 
4.5%
s 809
 
4.4%
, 795
 
4.3%
Other values (61) 6626
36.0%
Punctuation
ValueCountFrequency (%)
24
92.3%
1
 
3.8%
1
 
3.8%

partner_cbo
Text

MISSING 

Distinct359
Distinct (%)98.6%
Missing73
Missing (%)16.7%
Memory size73.6 KiB
2023-12-09T22:18:37.576804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length685
Median length216
Mean length128.3901099
Min length6

Characters and Unicode

Total characters46734
Distinct characters81
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique354 ?
Unique (%)97.3%

Sample

1st rowThe Henry Street Settlement; Asia Society; America Reads; Future Project; 21st Century Grant
2nd rowGrand Street Settlement, Henry Street Settlement, Educational Alliance, Gouveneur Hospital, The New Museum, Health and Hospital Corporation, College Summit, PENCIL,
3rd rowUniversity Settlement, Educational Alliance, CASALEAP, Project Stay.
4th rowNYCDOE Innovation Zone Lab Site, Grand Street Settlement, Learning Through an Expanded Arts Program (LeAP), NYU Gallatin Writing Project, Lower East Side Girls' Club, Lower East Side Family Alliance, Relationship Abuse Prevention Program (RAPP).
5th row7th Precinct Community Affairs, NYCWastele$$, Penny Harvest, Blood Drive, CASALEAP, University Settlement House, Henry Street Settlement, Toys for Tots
ValueCountFrequency (%)
the 154
 
2.5%
for 135
 
2.2%
and 132
 
2.1%
of 131
 
2.1%
new 119
 
1.9%
center 110
 
1.8%
program 106
 
1.7%
york 103
 
1.6%
college 90
 
1.4%
community 81
 
1.3%
Other values (1611) 5115
81.5%
2023-12-09T22:18:38.167108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5912
 
12.7%
e 3952
 
8.5%
o 3039
 
6.5%
n 2771
 
5.9%
r 2714
 
5.8%
i 2677
 
5.7%
t 2613
 
5.6%
a 2460
 
5.3%
s 1796
 
3.8%
l 1482
 
3.2%
Other values (71) 17318
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32173
68.8%
Uppercase Letter 6559
 
14.0%
Space Separator 5912
 
12.7%
Other Punctuation 1562
 
3.3%
Open Punctuation 163
 
0.3%
Close Punctuation 163
 
0.3%
Dash Punctuation 93
 
0.2%
Decimal Number 88
 
0.2%
Final Punctuation 17
 
< 0.1%
Currency Symbol 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3952
12.3%
o 3039
9.4%
n 2771
 
8.6%
r 2714
 
8.4%
i 2677
 
8.3%
t 2613
 
8.1%
a 2460
 
7.6%
s 1796
 
5.6%
l 1482
 
4.6%
c 1084
 
3.4%
Other values (16) 7585
23.6%
Uppercase Letter
ValueCountFrequency (%)
C 956
14.6%
S 642
 
9.8%
A 603
 
9.2%
P 469
 
7.2%
Y 333
 
5.1%
N 329
 
5.0%
B 297
 
4.5%
H 285
 
4.3%
E 281
 
4.3%
M 270
 
4.1%
Other values (16) 2094
31.9%
Decimal Number
ValueCountFrequency (%)
1 20
22.7%
0 12
13.6%
4 11
12.5%
2 11
12.5%
6 9
10.2%
3 9
10.2%
5 5
 
5.7%
9 5
 
5.7%
8 3
 
3.4%
7 3
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 1190
76.2%
. 156
 
10.0%
; 79
 
5.1%
' 55
 
3.5%
/ 30
 
1.9%
& 25
 
1.6%
: 18
 
1.2%
@ 5
 
0.3%
! 4
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 92
98.9%
1
 
1.1%
Final Punctuation
ValueCountFrequency (%)
16
94.1%
1
 
5.9%
Space Separator
ValueCountFrequency (%)
5912
100.0%
Open Punctuation
ValueCountFrequency (%)
( 163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38732
82.9%
Common 8002
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3952
 
10.2%
o 3039
 
7.8%
n 2771
 
7.2%
r 2714
 
7.0%
i 2677
 
6.9%
t 2613
 
6.7%
a 2460
 
6.4%
s 1796
 
4.6%
l 1482
 
3.8%
c 1084
 
2.8%
Other values (42) 14144
36.5%
Common
ValueCountFrequency (%)
5912
73.9%
, 1190
 
14.9%
( 163
 
2.0%
) 163
 
2.0%
. 156
 
1.9%
- 92
 
1.1%
; 79
 
1.0%
' 55
 
0.7%
/ 30
 
0.4%
& 25
 
0.3%
Other values (19) 137
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46715
> 99.9%
Punctuation 19
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5912
 
12.7%
e 3952
 
8.5%
o 3039
 
6.5%
n 2771
 
5.9%
r 2714
 
5.8%
i 2677
 
5.7%
t 2613
 
5.6%
a 2460
 
5.3%
s 1796
 
3.8%
l 1482
 
3.2%
Other values (67) 17299
37.0%
Punctuation
ValueCountFrequency (%)
16
84.2%
1
 
5.3%
1
 
5.3%
1
 
5.3%

partner_hospital
Text

MISSING 

Distinct186
Distinct (%)89.4%
Missing229
Missing (%)52.4%
Memory size32.1 KiB
2023-12-09T22:18:38.520245image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length683
Median length106
Mean length61.72115385
Min length10

Characters and Unicode

Total characters12838
Distinct characters62
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)82.7%

Sample

1st rowGouverneur Hospital (Turning Points)
2nd rowGouverneur Hospital, The Door, The Mount Sinai Adolescent Clinic
3rd rowGouvenuer's Hospital
4th rowSt. Luke’s-Roosevelt Hospital Center
5th rowMount Sinai Hospital
ValueCountFrequency (%)
hospital 173
 
10.3%
center 166
 
9.9%
medical 106
 
6.3%
health 62
 
3.7%
and 42
 
2.5%
clinic 41
 
2.4%
montefiore 36
 
2.1%
new 35
 
2.1%
island 28
 
1.7%
mount 24
 
1.4%
Other values (338) 964
57.5%
2023-12-09T22:18:39.053043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1469
 
11.4%
e 1292
 
10.1%
i 884
 
6.9%
t 875
 
6.8%
n 819
 
6.4%
o 798
 
6.2%
a 780
 
6.1%
l 691
 
5.4%
r 664
 
5.2%
s 548
 
4.3%
Other values (52) 4018
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9361
72.9%
Uppercase Letter 1610
 
12.5%
Space Separator 1469
 
11.4%
Other Punctuation 252
 
2.0%
Dash Punctuation 69
 
0.5%
Open Punctuation 37
 
0.3%
Close Punctuation 37
 
0.3%
Final Punctuation 2
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1292
13.8%
i 884
9.4%
t 875
9.3%
n 819
8.7%
o 798
8.5%
a 780
8.3%
l 691
7.4%
r 664
 
7.1%
s 548
 
5.9%
c 285
 
3.0%
Other values (14) 1725
18.4%
Uppercase Letter
ValueCountFrequency (%)
C 290
18.0%
H 281
17.5%
M 223
13.9%
S 135
8.4%
N 86
 
5.3%
L 61
 
3.8%
Y 59
 
3.7%
I 59
 
3.7%
P 51
 
3.2%
B 44
 
2.7%
Other values (14) 321
19.9%
Other Punctuation
ValueCountFrequency (%)
, 173
68.7%
. 42
 
16.7%
' 17
 
6.7%
& 8
 
3.2%
/ 8
 
3.2%
: 2
 
0.8%
; 2
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 68
98.6%
1
 
1.4%
Space Separator
ValueCountFrequency (%)
1469
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10971
85.5%
Common 1867
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1292
 
11.8%
i 884
 
8.1%
t 875
 
8.0%
n 819
 
7.5%
o 798
 
7.3%
a 780
 
7.1%
l 691
 
6.3%
r 664
 
6.1%
s 548
 
5.0%
C 290
 
2.6%
Other values (38) 3330
30.4%
Common
ValueCountFrequency (%)
1469
78.7%
, 173
 
9.3%
- 68
 
3.6%
. 42
 
2.2%
( 37
 
2.0%
) 37
 
2.0%
' 17
 
0.9%
& 8
 
0.4%
/ 8
 
0.4%
: 2
 
0.1%
Other values (4) 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12835
> 99.9%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1469
 
11.4%
e 1292
 
10.1%
i 884
 
6.9%
t 875
 
6.8%
n 819
 
6.4%
o 798
 
6.2%
a 780
 
6.1%
l 691
 
5.4%
r 664
 
5.2%
s 548
 
4.3%
Other values (50) 4015
31.3%
Punctuation
ValueCountFrequency (%)
2
66.7%
1
33.3%

partner_highered
Text

MISSING 

Distinct351
Distinct (%)91.4%
Missing53
Missing (%)12.1%
Memory size74.1 KiB
2023-12-09T22:18:39.417897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length953
Median length205.5
Mean length121.6901042
Min length12

Characters and Unicode

Total characters46729
Distinct characters67
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)87.5%

Sample

1st rowNew York University
2nd rowNew York University, CUNY Baruch College, Parsons School of Design, St. John's University, LaGuardia Community College, BMCC,
3rd rowColumbia Teachers College, New York University, The New School, John Jay College, Hunter College, Borough of Manhattan Community College (BMCC) Upward Bound, Bard College, Gettysburg College, Fashion Institute of Technology (FIT) Summer Program, At Home in College CUNY Program.
4th rowNew York University (NYU), Sarah Lawrence College, Williams College, Borough of Manhattan Community College (BMCC), Empire State College, Minister of Education of Quebec, International Remote Networked Schools Project
5th rowHunter College, New York University, Cornell University, St. John's University, Pace University, Baruch College
ValueCountFrequency (%)
college 1000
 
15.9%
university 610
 
9.7%
of 350
 
5.6%
york 295
 
4.7%
new 293
 
4.7%
community 177
 
2.8%
city 146
 
2.3%
the 106
 
1.7%
and 89
 
1.4%
columbia 81
 
1.3%
Other values (690) 3153
50.0%
2023-12-09T22:18:39.955112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5916
 
12.7%
e 4681
 
10.0%
o 3713
 
7.9%
l 2823
 
6.0%
i 2480
 
5.3%
n 2426
 
5.2%
r 2261
 
4.8%
t 2188
 
4.7%
C 1658
 
3.5%
s 1558
 
3.3%
Other values (57) 17025
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32753
70.1%
Uppercase Letter 6133
 
13.1%
Space Separator 5916
 
12.7%
Other Punctuation 1566
 
3.4%
Open Punctuation 148
 
0.3%
Close Punctuation 148
 
0.3%
Dash Punctuation 40
 
0.1%
Final Punctuation 21
 
< 0.1%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4681
14.3%
o 3713
11.3%
l 2823
 
8.6%
i 2480
 
7.6%
n 2426
 
7.4%
r 2261
 
6.9%
t 2188
 
6.7%
s 1558
 
4.8%
a 1532
 
4.7%
g 1492
 
4.6%
Other values (15) 7599
23.2%
Uppercase Letter
ValueCountFrequency (%)
C 1658
27.0%
U 814
13.3%
N 535
 
8.7%
Y 474
 
7.7%
S 377
 
6.1%
T 287
 
4.7%
B 242
 
3.9%
M 199
 
3.2%
P 184
 
3.0%
L 183
 
3.0%
Other values (15) 1180
19.2%
Other Punctuation
ValueCountFrequency (%)
, 1282
81.9%
. 132
 
8.4%
; 64
 
4.1%
' 49
 
3.1%
: 15
 
1.0%
/ 13
 
0.8%
& 7
 
0.4%
@ 4
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
1 1
25.0%
0 1
25.0%
9 1
25.0%
Space Separator
ValueCountFrequency (%)
5916
100.0%
Open Punctuation
ValueCountFrequency (%)
( 148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Final Punctuation
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38886
83.2%
Common 7843
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4681
 
12.0%
o 3713
 
9.5%
l 2823
 
7.3%
i 2480
 
6.4%
n 2426
 
6.2%
r 2261
 
5.8%
t 2188
 
5.6%
C 1658
 
4.3%
s 1558
 
4.0%
a 1532
 
3.9%
Other values (40) 13566
34.9%
Common
ValueCountFrequency (%)
5916
75.4%
, 1282
 
16.3%
( 148
 
1.9%
) 148
 
1.9%
. 132
 
1.7%
; 64
 
0.8%
' 49
 
0.6%
- 40
 
0.5%
21
 
0.3%
: 15
 
0.2%
Other values (7) 28
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46708
> 99.9%
Punctuation 21
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5916
 
12.7%
e 4681
 
10.0%
o 3713
 
7.9%
l 2823
 
6.0%
i 2480
 
5.3%
n 2426
 
5.2%
r 2261
 
4.8%
t 2188
 
4.7%
C 1658
 
3.5%
s 1558
 
3.3%
Other values (56) 17004
36.4%
Punctuation
ValueCountFrequency (%)
21
100.0%

partner_cultural
Text

MISSING 

Distinct311
Distinct (%)99.7%
Missing125
Missing (%)28.6%
Memory size61.0 KiB
2023-12-09T22:18:40.367274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length683
Median length173
Mean length121.4230769
Min length1

Characters and Unicode

Total characters37884
Distinct characters79
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)99.4%

Sample

1st rowAsia Society
2nd rowDance Film Association, Dance Makers Film Workshop, Theatre Development Fund, Hester Street Collaborative Public Arts Project, The New Museum, The Whitney Museum, The International Center for Photography, Cooper Union
3rd rowUniversity Settlement, The Possibility Project, Bridging Education and Art Together (BEAT), International Center for Photography, ArtsConnection, Arts in Action Program, Internship Program, Loisaida Art Gallery located within the school and online, Loisaidaartgallery.org, Five Boroughs Foundation of Photography, the Nuyorican Poet’s Café.
4th rowYoung Audiences, The National Arts Club, Educational Network of Artists and Creative Theatre (ENACT), Creative Cookie
5th rowVH1, Dancing Classrooms, Center for Arts Education, New Museum, School of Visual Arts, The Jazz Standard, New York State School Music Associations, American Choral Directors Association; Visiting Artists: Jeff Lederer, Wynton Marsalis, Monica Buffington, Ralph Alessi
ValueCountFrequency (%)
the 242
 
4.5%
of 240
 
4.5%
museum 207
 
3.9%
arts 168
 
3.1%
center 134
 
2.5%
art 118
 
2.2%
for 98
 
1.8%
theater 95
 
1.8%
theatre 92
 
1.7%
new 87
 
1.6%
Other values (1160) 3865
72.3%
2023-12-09T22:18:40.953979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5034
 
13.3%
e 3283
 
8.7%
r 2451
 
6.5%
o 2415
 
6.4%
t 2312
 
6.1%
a 2155
 
5.7%
n 2097
 
5.5%
i 1714
 
4.5%
s 1388
 
3.7%
l 1220
 
3.2%
Other values (69) 13815
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26401
69.7%
Space Separator 5034
 
13.3%
Uppercase Letter 4868
 
12.8%
Other Punctuation 1232
 
3.3%
Open Punctuation 117
 
0.3%
Close Punctuation 116
 
0.3%
Dash Punctuation 62
 
0.2%
Decimal Number 45
 
0.1%
Final Punctuation 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3283
12.4%
r 2451
 
9.3%
o 2415
 
9.1%
t 2312
 
8.8%
a 2155
 
8.2%
n 2097
 
7.9%
i 1714
 
6.5%
s 1388
 
5.3%
l 1220
 
4.6%
u 1146
 
4.3%
Other values (18) 6220
23.6%
Uppercase Letter
ValueCountFrequency (%)
A 647
13.3%
M 526
 
10.8%
C 526
 
10.8%
T 449
 
9.2%
S 329
 
6.8%
P 267
 
5.5%
B 224
 
4.6%
N 220
 
4.5%
E 181
 
3.7%
F 177
 
3.6%
Other values (16) 1322
27.2%
Other Punctuation
ValueCountFrequency (%)
, 1048
85.1%
. 91
 
7.4%
; 29
 
2.4%
' 28
 
2.3%
/ 14
 
1.1%
: 12
 
1.0%
& 6
 
0.5%
! 3
 
0.2%
@ 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 14
31.1%
1 11
24.4%
9 7
15.6%
0 6
13.3%
4 3
 
6.7%
5 2
 
4.4%
8 1
 
2.2%
6 1
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 61
98.4%
1
 
1.6%
Space Separator
ValueCountFrequency (%)
5034
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Final Punctuation
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31269
82.5%
Common 6615
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3283
 
10.5%
r 2451
 
7.8%
o 2415
 
7.7%
t 2312
 
7.4%
a 2155
 
6.9%
n 2097
 
6.7%
i 1714
 
5.5%
s 1388
 
4.4%
l 1220
 
3.9%
u 1146
 
3.7%
Other values (44) 11088
35.5%
Common
ValueCountFrequency (%)
5034
76.1%
, 1048
 
15.8%
( 117
 
1.8%
) 116
 
1.8%
. 91
 
1.4%
- 61
 
0.9%
; 29
 
0.4%
' 28
 
0.4%
2 14
 
0.2%
/ 14
 
0.2%
Other values (15) 63
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37872
> 99.9%
Punctuation 8
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5034
 
13.3%
e 3283
 
8.7%
r 2451
 
6.5%
o 2415
 
6.4%
t 2312
 
6.1%
a 2155
 
5.7%
n 2097
 
5.5%
i 1714
 
4.5%
s 1388
 
3.7%
l 1220
 
3.2%
Other values (65) 13803
36.4%
Punctuation
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
None
ValueCountFrequency (%)
ñ 3
75.0%
é 1
 
25.0%

partner_nonprofit
Text

MISSING 

Distinct287
Distinct (%)93.5%
Missing130
Missing (%)29.7%
Memory size53.7 KiB
2023-12-09T22:18:41.344878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length996
Median length154
Mean length97.86319218
Min length1

Characters and Unicode

Total characters30044
Distinct characters77
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique279 ?
Unique (%)90.9%

Sample

1st rowHeart of America Foundation
2nd rowW!SE, Big Brothers Big Sisters, Peer Health Exchange, New York Public Library, United Way NYC, Network for Teaching Entrepreneurship (NFTE),
3rd rowCollege Bound Initiative, Center for Collaborative Education, Stoked, PENCIL, Fund for Public Schools, Ramapo, Facing History and Ourselves, National Lab Day, Chess-in- the-Schools, Sponsors for Educational Opportunity (SEO), Lower East Side Ecology Center, Coalition of Essential Schools, Upward Bound, CARA (College Access: Research & Action).
4th rowCollege for Every Student (CFES), Morningside Center for Teaching Social Responsibility, Australian United States Services in Education (AUSSIE), Careers through Culinary Arts Program (C-CAP), Childsight
5th rowAfter 3
ValueCountFrequency (%)
for 169
 
4.1%
the 119
 
2.9%
new 116
 
2.8%
of 83
 
2.0%
york 79
 
1.9%
foundation 69
 
1.7%
and 59
 
1.4%
schools 50
 
1.2%
center 49
 
1.2%
program 42
 
1.0%
Other values (1170) 3252
79.6%
2023-12-09T22:18:41.919414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3780
 
12.6%
e 2453
 
8.2%
o 2042
 
6.8%
n 1851
 
6.2%
i 1741
 
5.8%
r 1738
 
5.8%
t 1670
 
5.6%
a 1551
 
5.2%
s 1159
 
3.9%
l 888
 
3.0%
Other values (67) 11171
37.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20631
68.7%
Uppercase Letter 4301
 
14.3%
Space Separator 3780
 
12.6%
Other Punctuation 978
 
3.3%
Close Punctuation 124
 
0.4%
Open Punctuation 124
 
0.4%
Dash Punctuation 56
 
0.2%
Decimal Number 37
 
0.1%
Final Punctuation 12
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2453
11.9%
o 2042
9.9%
n 1851
 
9.0%
i 1741
 
8.4%
r 1738
 
8.4%
t 1670
 
8.1%
a 1551
 
7.5%
s 1159
 
5.6%
l 888
 
4.3%
c 799
 
3.9%
Other values (16) 4739
23.0%
Uppercase Letter
ValueCountFrequency (%)
C 548
12.7%
A 420
 
9.8%
S 377
 
8.8%
N 330
 
7.7%
P 272
 
6.3%
E 248
 
5.8%
I 205
 
4.8%
F 195
 
4.5%
Y 179
 
4.2%
T 174
 
4.0%
Other values (16) 1353
31.5%
Other Punctuation
ValueCountFrequency (%)
, 778
79.6%
. 92
 
9.4%
' 32
 
3.3%
; 22
 
2.2%
/ 18
 
1.8%
& 15
 
1.5%
: 11
 
1.1%
! 9
 
0.9%
% 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 11
29.7%
1 9
24.3%
2 5
13.5%
6 3
 
8.1%
3 3
 
8.1%
5 2
 
5.4%
8 2
 
5.4%
9 1
 
2.7%
4 1
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 55
98.2%
1
 
1.8%
Space Separator
ValueCountFrequency (%)
3780
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Final Punctuation
ValueCountFrequency (%)
12
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24932
83.0%
Common 5112
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2453
 
9.8%
o 2042
 
8.2%
n 1851
 
7.4%
i 1741
 
7.0%
r 1738
 
7.0%
t 1670
 
6.7%
a 1551
 
6.2%
s 1159
 
4.6%
l 888
 
3.6%
c 799
 
3.2%
Other values (42) 9040
36.3%
Common
ValueCountFrequency (%)
3780
73.9%
, 778
 
15.2%
) 124
 
2.4%
( 124
 
2.4%
. 92
 
1.8%
- 55
 
1.1%
' 32
 
0.6%
; 22
 
0.4%
/ 18
 
0.4%
& 15
 
0.3%
Other values (15) 72
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30030
> 99.9%
Punctuation 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3780
 
12.6%
e 2453
 
8.2%
o 2042
 
6.8%
n 1851
 
6.2%
i 1741
 
5.8%
r 1738
 
5.8%
t 1670
 
5.6%
a 1551
 
5.2%
s 1159
 
3.9%
l 888
 
3.0%
Other values (64) 11157
37.2%
Punctuation
ValueCountFrequency (%)
12
85.7%
1
 
7.1%
1
 
7.1%

partner_corporate
Text

MISSING 

Distinct199
Distinct (%)98.0%
Missing234
Missing (%)53.5%
Memory size33.0 KiB
2023-12-09T22:18:42.337577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length648
Median length140
Mean length70.31527094
Min length1

Characters and Unicode

Total characters14274
Distinct characters72
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)96.1%

Sample

1st rowDeloitte LLP Consulting and Financial Services, Kaplan, Two Sigma Technology and Consulting, PENCIL,
2nd rowPrudential Securities, Moore Capital, Morgan Stanley, Barclay Intercontinental Hotels, Supreme, IBM, Guardian Insurance, Guggenheim Partners.
3rd rowEstée Lauder
4th rowTime Warner Cable, Google, IBM, MET Project, Sony, Vital NY
5th rowPENCIL
ValueCountFrequency (%)
48
 
2.5%
and 42
 
2.2%
of 32
 
1.7%
the 31
 
1.6%
inc 29
 
1.5%
llp 24
 
1.2%
new 23
 
1.2%
york 20
 
1.0%
foundation 18
 
0.9%
for 17
 
0.9%
Other values (994) 1653
85.3%
2023-12-09T22:18:42.940330image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1734
 
12.1%
e 1047
 
7.3%
o 932
 
6.5%
n 927
 
6.5%
a 845
 
5.9%
i 840
 
5.9%
r 826
 
5.8%
t 750
 
5.3%
s 631
 
4.4%
l 465
 
3.3%
Other values (62) 5277
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9771
68.5%
Uppercase Letter 2018
 
14.1%
Space Separator 1734
 
12.1%
Other Punctuation 646
 
4.5%
Close Punctuation 29
 
0.2%
Open Punctuation 29
 
0.2%
Dash Punctuation 24
 
0.2%
Decimal Number 18
 
0.1%
Final Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1047
10.7%
o 932
9.5%
n 927
9.5%
a 845
 
8.6%
i 840
 
8.6%
r 826
 
8.5%
t 750
 
7.7%
s 631
 
6.5%
l 465
 
4.8%
c 371
 
3.8%
Other values (17) 2137
21.9%
Uppercase Letter
ValueCountFrequency (%)
C 225
 
11.1%
S 161
 
8.0%
A 156
 
7.7%
M 129
 
6.4%
L 128
 
6.3%
T 126
 
6.2%
P 121
 
6.0%
B 119
 
5.9%
I 103
 
5.1%
N 95
 
4.7%
Other values (16) 655
32.5%
Other Punctuation
ValueCountFrequency (%)
, 454
70.3%
. 79
 
12.2%
& 46
 
7.1%
; 33
 
5.1%
' 16
 
2.5%
/ 13
 
2.0%
: 5
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 6
33.3%
1 5
27.8%
3 3
16.7%
2 3
16.7%
5 1
 
5.6%
Space Separator
ValueCountFrequency (%)
1734
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11789
82.6%
Common 2485
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1047
 
8.9%
o 932
 
7.9%
n 927
 
7.9%
a 845
 
7.2%
i 840
 
7.1%
r 826
 
7.0%
t 750
 
6.4%
s 631
 
5.4%
l 465
 
3.9%
c 371
 
3.1%
Other values (43) 4155
35.2%
Common
ValueCountFrequency (%)
1734
69.8%
, 454
 
18.3%
. 79
 
3.2%
& 46
 
1.9%
; 33
 
1.3%
) 29
 
1.2%
( 29
 
1.2%
- 24
 
1.0%
' 16
 
0.6%
/ 13
 
0.5%
Other values (9) 28
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14269
> 99.9%
Punctuation 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1734
 
12.2%
e 1047
 
7.3%
o 932
 
6.5%
n 927
 
6.5%
a 845
 
5.9%
i 840
 
5.9%
r 826
 
5.8%
t 750
 
5.3%
s 631
 
4.4%
l 465
 
3.3%
Other values (60) 5272
36.9%
Punctuation
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
é 2
100.0%

partner_financial
Text

MISSING 

Distinct69
Distinct (%)85.2%
Missing356
Missing (%)81.5%
Memory size19.8 KiB
2023-12-09T22:18:43.284914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length619
Median length61
Mean length50.03703704
Min length8

Characters and Unicode

Total characters4053
Distinct characters61
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)75.3%

Sample

1st rowBank of America
2nd rowMunicipal Credit Union
3rd rowBNP Paribas
4th rowThe Federal Reserve Bank, New York State Banking Department
5th rowMorgan Stanley mentoring program
ValueCountFrequency (%)
bank 42
 
7.2%
of 20
 
3.4%
chase 17
 
2.9%
16
 
2.7%
capital 13
 
2.2%
morgan 13
 
2.2%
york 12
 
2.1%
new 12
 
2.1%
federal 12
 
2.1%
one 11
 
1.9%
Other values (236) 414
71.1%
2023-12-09T22:18:43.863363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
501
 
12.4%
e 340
 
8.4%
a 307
 
7.6%
n 292
 
7.2%
i 237
 
5.8%
r 226
 
5.6%
t 207
 
5.1%
o 204
 
5.0%
s 151
 
3.7%
c 102
 
2.5%
Other values (51) 1486
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2826
69.7%
Uppercase Letter 575
 
14.2%
Space Separator 501
 
12.4%
Other Punctuation 109
 
2.7%
Open Punctuation 14
 
0.3%
Close Punctuation 14
 
0.3%
Dash Punctuation 13
 
0.3%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 340
12.0%
a 307
10.9%
n 292
10.3%
i 237
 
8.4%
r 226
 
8.0%
t 207
 
7.3%
o 204
 
7.2%
s 151
 
5.3%
c 102
 
3.6%
l 99
 
3.5%
Other values (15) 661
23.4%
Uppercase Letter
ValueCountFrequency (%)
C 79
13.7%
B 70
12.2%
S 56
 
9.7%
M 41
 
7.1%
A 40
 
7.0%
P 34
 
5.9%
F 34
 
5.9%
R 25
 
4.3%
I 24
 
4.2%
E 24
 
4.2%
Other values (14) 148
25.7%
Other Punctuation
ValueCountFrequency (%)
, 74
67.9%
. 14
 
12.8%
& 10
 
9.2%
: 5
 
4.6%
' 3
 
2.8%
! 2
 
1.8%
; 1
 
0.9%
Space Separator
ValueCountFrequency (%)
501
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3401
83.9%
Common 652
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 340
 
10.0%
a 307
 
9.0%
n 292
 
8.6%
i 237
 
7.0%
r 226
 
6.6%
t 207
 
6.1%
o 204
 
6.0%
s 151
 
4.4%
c 102
 
3.0%
l 99
 
2.9%
Other values (39) 1236
36.3%
Common
ValueCountFrequency (%)
501
76.8%
, 74
 
11.3%
. 14
 
2.1%
( 14
 
2.1%
) 14
 
2.1%
- 13
 
2.0%
& 10
 
1.5%
: 5
 
0.8%
' 3
 
0.5%
! 2
 
0.3%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4052
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
501
 
12.4%
e 340
 
8.4%
a 307
 
7.6%
n 292
 
7.2%
i 237
 
5.8%
r 226
 
5.6%
t 207
 
5.1%
o 204
 
5.0%
s 151
 
3.7%
c 102
 
2.5%
Other values (50) 1485
36.6%
Punctuation
ValueCountFrequency (%)
1
100.0%

partner_other
Text

MISSING 

Distinct191
Distinct (%)99.0%
Missing244
Missing (%)55.8%
Memory size38.1 KiB
2023-12-09T22:18:44.314432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length692
Median length123
Mean length85.39378238
Min length1

Characters and Unicode

Total characters16481
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)97.9%

Sample

1st rowUnited Nations
2nd rowMovement Research
3rd rowBrooklyn Boulders (Rock Climbing)
4th rowCASALEAP, Beacon
5th rowNew York Academy of Sciences
ValueCountFrequency (%)
of 65
 
2.9%
new 62
 
2.7%
and 58
 
2.5%
york 58
 
2.5%
the 56
 
2.5%
for 40
 
1.8%
school 34
 
1.5%
office 27
 
1.2%
city 26
 
1.1%
in 24
 
1.1%
Other values (966) 1827
80.2%
2023-12-09T22:18:44.926463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2084
 
12.6%
e 1398
 
8.5%
o 1131
 
6.9%
n 1038
 
6.3%
t 994
 
6.0%
r 965
 
5.9%
i 954
 
5.8%
a 926
 
5.6%
s 657
 
4.0%
l 516
 
3.1%
Other values (66) 5818
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11757
71.3%
Space Separator 2084
 
12.6%
Uppercase Letter 1992
 
12.1%
Other Punctuation 445
 
2.7%
Open Punctuation 57
 
0.3%
Close Punctuation 57
 
0.3%
Dash Punctuation 40
 
0.2%
Decimal Number 31
 
0.2%
Final Punctuation 17
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1398
11.9%
o 1131
9.6%
n 1038
 
8.8%
t 994
 
8.5%
r 965
 
8.2%
i 954
 
8.1%
a 926
 
7.9%
s 657
 
5.6%
l 516
 
4.4%
c 480
 
4.1%
Other values (16) 2698
22.9%
Uppercase Letter
ValueCountFrequency (%)
C 253
12.7%
S 209
 
10.5%
A 174
 
8.7%
N 142
 
7.1%
P 122
 
6.1%
T 107
 
5.4%
Y 103
 
5.2%
E 94
 
4.7%
B 88
 
4.4%
I 85
 
4.3%
Other values (15) 615
30.9%
Other Punctuation
ValueCountFrequency (%)
, 302
67.9%
. 72
 
16.2%
' 23
 
5.2%
; 21
 
4.7%
: 9
 
2.0%
/ 8
 
1.8%
& 7
 
1.6%
! 2
 
0.4%
@ 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 9
29.0%
2 5
16.1%
0 5
16.1%
3 4
12.9%
6 3
 
9.7%
8 3
 
9.7%
5 1
 
3.2%
4 1
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 36
90.0%
3
 
7.5%
1
 
2.5%
Space Separator
ValueCountFrequency (%)
2084
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Final Punctuation
ValueCountFrequency (%)
17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13749
83.4%
Common 2732
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1398
 
10.2%
o 1131
 
8.2%
n 1038
 
7.5%
t 994
 
7.2%
r 965
 
7.0%
i 954
 
6.9%
a 926
 
6.7%
s 657
 
4.8%
l 516
 
3.8%
c 480
 
3.5%
Other values (41) 4690
34.1%
Common
ValueCountFrequency (%)
2084
76.3%
, 302
 
11.1%
. 72
 
2.6%
( 57
 
2.1%
) 57
 
2.1%
- 36
 
1.3%
' 23
 
0.8%
; 21
 
0.8%
17
 
0.6%
: 9
 
0.3%
Other values (15) 54
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16460
99.9%
Punctuation 21
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2084
 
12.7%
e 1398
 
8.5%
o 1131
 
6.9%
n 1038
 
6.3%
t 994
 
6.0%
r 965
 
5.9%
i 954
 
5.8%
a 926
 
5.6%
s 657
 
4.0%
l 516
 
3.1%
Other values (63) 5797
35.2%
Punctuation
ValueCountFrequency (%)
17
81.0%
3
 
14.3%
1
 
4.8%

addtl_info1
Text

MISSING 

Distinct21
Distinct (%)10.5%
Missing237
Missing (%)54.2%
Memory size38.7 KiB
2023-12-09T22:18:45.180442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length349
Median length73
Mean length102.495
Min length23

Characters and Unicode

Total characters20499
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)7.5%

Sample

1st rowiLearnNYC: Program for expanded online coursework and self-paced learning
2nd rowiLearnNYC: Program for expanded online coursework and self-paced learning
3rd rowiLearnNYC: Program for expanded online coursework and self-paced learning
4th rowiLearnNYC: Program for expanded online coursework and self-paced learning
5th rowiLearnNYC: Program for expanded online coursework and self-paced learning
ValueCountFrequency (%)
and 267
10.7%
learning 233
9.3%
program 227
9.1%
ilearnnyc 199
 
8.0%
for 199
 
8.0%
expanded 199
 
8.0%
online 199
 
8.0%
coursework 199
 
8.0%
self-paced 199
 
8.0%
school 68
 
2.7%
Other values (26) 505
20.2%
2023-12-09T22:18:45.578169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2294
 
11.2%
e 2156
 
10.5%
r 1824
 
8.9%
n 1818
 
8.9%
a 1556
 
7.6%
o 1405
 
6.9%
d 1004
 
4.9%
i 964
 
4.7%
l 803
 
3.9%
s 674
 
3.3%
Other values (32) 6001
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16380
79.9%
Space Separator 2294
 
11.2%
Uppercase Letter 1240
 
6.0%
Other Punctuation 386
 
1.9%
Dash Punctuation 199
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2156
13.2%
r 1824
11.1%
n 1818
11.1%
a 1556
9.5%
o 1405
 
8.6%
d 1004
 
6.1%
i 964
 
5.9%
l 803
 
4.9%
s 674
 
4.1%
g 596
 
3.6%
Other values (14) 3580
21.9%
Uppercase Letter
ValueCountFrequency (%)
C 243
19.6%
P 229
18.5%
Y 199
16.0%
L 199
16.0%
N 199
16.0%
S 69
 
5.6%
O 46
 
3.7%
D 15
 
1.2%
E 14
 
1.1%
W 12
 
1.0%
Other values (3) 15
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 233
60.4%
; 85
 
22.0%
, 68
 
17.6%
Space Separator
ValueCountFrequency (%)
2294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17620
86.0%
Common 2879
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2156
12.2%
r 1824
 
10.4%
n 1818
 
10.3%
a 1556
 
8.8%
o 1405
 
8.0%
d 1004
 
5.7%
i 964
 
5.5%
l 803
 
4.6%
s 674
 
3.8%
g 596
 
3.4%
Other values (27) 4820
27.4%
Common
ValueCountFrequency (%)
2294
79.7%
: 233
 
8.1%
- 199
 
6.9%
; 85
 
3.0%
, 68
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2294
 
11.2%
e 2156
 
10.5%
r 1824
 
8.9%
n 1818
 
8.9%
a 1556
 
7.6%
o 1405
 
6.9%
d 1004
 
4.9%
i 964
 
4.7%
l 803
 
3.9%
s 674
 
3.3%
Other values (32) 6001
29.3%

addtl_info2
Text

MISSING 

Distinct343
Distinct (%)89.6%
Missing54
Missing (%)12.4%
Memory size93.0 KiB
2023-12-09T22:18:45.928658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1309
Median length287
Mean length173.0443864
Min length16

Characters and Unicode

Total characters66276
Distinct characters75
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique337 ?
Unique (%)88.0%

Sample

1st rowIncoming students are expected to attend school orientation in June; Internships are encouraged and supported; Extra academic support is available daily for all students in all subjects.
2nd rowStudents present and defend their work to committees twice a year through our portfolio roundtable presentations; Students complete Performance-based Assessment Tasks (PBATs) such as a college-level history research paper and a student-designed science experiment as a replacement for the math, science and history Regents Exams. Students do take the ELA Regents Exam. The state recognizes these PBATs as a replacement for the Regents Exams.; Internship Opportunities
3rd rowStudents Dress for Success; Summer Bridge to Success Program for incoming students in July offers HS credits; Saturday Success Academy Regents Prep; On-site Placement and Referral Office for Summer Youth Employment Program; Parent Resource Room; College Trips & Tours and Free Application for Federal Student Aid (FAFSA) Application Workshops
4th rowDress Code Required: Business Casual - shirt/blouse, khaki, corduroy or dark denim (navy, black, brown, dark gray) pants, dress slacks/skirt/dress. On Assembly Days, students wear job interview clothing (Boys - shirt and tie, optional blazer); Community Service Requirement - All Upper School students are required to complete 60 hours of Community Service; Ninth grade math and science are single gender classes.
5th rowOur student body is composed of deaf, hard-of-hearing and hearing students; Our students graduate with bilingual language proficiency (American Sign Language and English); ASL classes offered to parents and the community; Internship Opportunities
ValueCountFrequency (%)
required 257
 
2.8%
opportunities 228
 
2.5%
and 213
 
2.4%
internship 198
 
2.2%
school 190
 
2.1%
black 186
 
2.1%
or 185
 
2.0%
program 175
 
1.9%
for 174
 
1.9%
shirt 154
 
1.7%
Other values (1366) 7068
78.3%
2023-12-09T22:18:46.468655image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8645
 
13.0%
e 5937
 
9.0%
r 4647
 
7.0%
t 4190
 
6.3%
o 4022
 
6.1%
i 3849
 
5.8%
s 3832
 
5.8%
n 3522
 
5.3%
a 3421
 
5.2%
d 2137
 
3.2%
Other values (65) 22074
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51170
77.2%
Space Separator 8645
 
13.0%
Uppercase Letter 3599
 
5.4%
Other Punctuation 2067
 
3.1%
Decimal Number 312
 
0.5%
Dash Punctuation 254
 
0.4%
Open Punctuation 110
 
0.2%
Close Punctuation 110
 
0.2%
Final Punctuation 7
 
< 0.1%
Initial Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5937
11.6%
r 4647
 
9.1%
t 4190
 
8.2%
o 4022
 
7.9%
i 3849
 
7.5%
s 3832
 
7.5%
n 3522
 
6.9%
a 3421
 
6.7%
d 2137
 
4.2%
l 1996
 
3.9%
Other values (16) 13617
26.6%
Uppercase Letter
ValueCountFrequency (%)
S 531
14.8%
O 370
10.3%
P 360
10.0%
C 326
9.1%
R 311
8.6%
A 256
 
7.1%
I 254
 
7.1%
D 211
 
5.9%
E 154
 
4.3%
U 123
 
3.4%
Other values (14) 703
19.5%
Decimal Number
ValueCountFrequency (%)
0 95
30.4%
1 46
14.7%
2 45
14.4%
3 30
 
9.6%
5 29
 
9.3%
4 20
 
6.4%
9 17
 
5.4%
8 14
 
4.5%
6 11
 
3.5%
7 5
 
1.6%
Other Punctuation
ValueCountFrequency (%)
; 660
31.9%
, 583
28.2%
: 343
16.6%
/ 269
13.0%
. 174
 
8.4%
' 27
 
1.3%
& 10
 
0.5%
@ 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 242
95.3%
12
 
4.7%
Space Separator
ValueCountFrequency (%)
8645
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Final Punctuation
ValueCountFrequency (%)
7
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54769
82.6%
Common 11507
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5937
 
10.8%
r 4647
 
8.5%
t 4190
 
7.7%
o 4022
 
7.3%
i 3849
 
7.0%
s 3832
 
7.0%
n 3522
 
6.4%
a 3421
 
6.2%
d 2137
 
3.9%
l 1996
 
3.6%
Other values (40) 17216
31.4%
Common
ValueCountFrequency (%)
8645
75.1%
; 660
 
5.7%
, 583
 
5.1%
: 343
 
3.0%
/ 269
 
2.3%
- 242
 
2.1%
. 174
 
1.5%
( 110
 
1.0%
) 110
 
1.0%
0 95
 
0.8%
Other values (15) 276
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66255
> 99.9%
Punctuation 21
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8645
 
13.0%
e 5937
 
9.0%
r 4647
 
7.0%
t 4190
 
6.3%
o 4022
 
6.1%
i 3849
 
5.8%
s 3832
 
5.8%
n 3522
 
5.3%
a 3421
 
5.2%
d 2137
 
3.2%
Other values (62) 22053
33.3%
Punctuation
ValueCountFrequency (%)
12
57.1%
7
33.3%
2
 
9.5%
Distinct42
Distinct (%)9.7%
Missing4
Missing (%)0.9%
Memory size27.3 KiB
2023-12-09T22:18:46.678354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3031
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)5.1%

Sample

1st row8:30 AM
2nd row8:15 AM
3rd row8:30 AM
4th row8:00 AM
5th row8:15 AM
ValueCountFrequency (%)
am 433
50.0%
8:00 141
 
16.3%
8:30 70
 
8.1%
8:15 51
 
5.9%
8:45 31
 
3.6%
9:00 24
 
2.8%
8:20 20
 
2.3%
8:10 12
 
1.4%
8:40 10
 
1.2%
7:45 10
 
1.2%
Other values (33) 64
 
7.4%
2023-12-09T22:18:46.998717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 467
15.4%
: 433
14.3%
433
14.3%
A 433
14.3%
M 433
14.3%
8 376
12.4%
5 136
 
4.5%
3 87
 
2.9%
1 73
 
2.4%
4 58
 
1.9%
Other values (3) 102
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1299
42.9%
Uppercase Letter 866
28.6%
Other Punctuation 433
 
14.3%
Space Separator 433
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 467
36.0%
8 376
28.9%
5 136
 
10.5%
3 87
 
6.7%
1 73
 
5.6%
4 58
 
4.5%
2 37
 
2.8%
9 34
 
2.6%
7 31
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
A 433
50.0%
M 433
50.0%
Other Punctuation
ValueCountFrequency (%)
: 433
100.0%
Space Separator
ValueCountFrequency (%)
433
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2165
71.4%
Latin 866
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 467
21.6%
: 433
20.0%
433
20.0%
8 376
17.4%
5 136
 
6.3%
3 87
 
4.0%
1 73
 
3.4%
4 58
 
2.7%
2 37
 
1.7%
9 34
 
1.6%
Latin
ValueCountFrequency (%)
A 433
50.0%
M 433
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3031
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 467
15.4%
: 433
14.3%
433
14.3%
A 433
14.3%
M 433
14.3%
8 376
12.4%
5 136
 
4.5%
3 87
 
2.9%
1 73
 
2.4%
4 58
 
1.9%
Other values (3) 102
 
3.4%
Distinct64
Distinct (%)14.8%
Missing4
Missing (%)0.9%
Memory size27.3 KiB
2023-12-09T22:18:47.239748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3031
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)7.2%

Sample

1st row3:30 PM
2nd row3:15 PM
3rd row3:30 PM
4th row3:30 PM
5th row4:00 PM
ValueCountFrequency (%)
pm 433
50.0%
3:00 67
 
7.7%
3:30 54
 
6.2%
3:15 37
 
4.3%
3:45 32
 
3.7%
4:00 25
 
2.9%
2:45 23
 
2.7%
2:20 19
 
2.2%
2:30 18
 
2.1%
3:20 18
 
2.1%
Other values (55) 140
 
16.2%
2023-12-09T22:18:47.592985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 433
14.3%
433
14.3%
P 433
14.3%
M 433
14.3%
3 385
12.7%
0 364
12.0%
5 162
 
5.3%
2 161
 
5.3%
4 133
 
4.4%
1 67
 
2.2%
Other values (4) 27
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1299
42.9%
Uppercase Letter 866
28.6%
Other Punctuation 433
 
14.3%
Space Separator 433
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 385
29.6%
0 364
28.0%
5 162
12.5%
2 161
12.4%
4 133
 
10.2%
1 67
 
5.2%
7 9
 
0.7%
6 8
 
0.6%
8 6
 
0.5%
9 4
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
P 433
50.0%
M 433
50.0%
Other Punctuation
ValueCountFrequency (%)
: 433
100.0%
Space Separator
ValueCountFrequency (%)
433
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2165
71.4%
Latin 866
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
: 433
20.0%
433
20.0%
3 385
17.8%
0 364
16.8%
5 162
 
7.5%
2 161
 
7.4%
4 133
 
6.1%
1 67
 
3.1%
7 9
 
0.4%
6 8
 
0.4%
Other values (2) 10
 
0.5%
Latin
ValueCountFrequency (%)
P 433
50.0%
M 433
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3031
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 433
14.3%
433
14.3%
P 433
14.3%
M 433
14.3%
3 385
12.7%
0 364
12.0%
5 162
 
5.3%
2 161
 
5.3%
4 133
 
4.4%
1 67
 
2.2%
Other values (4) 27
 
0.9%

se_services
Text

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size68.0 KiB
2023-12-09T22:18:47.811320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length102
Mean length102
Min length102

Characters and Unicode

Total characters44574
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
2nd rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
3rd rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
4th rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
5th rowThis school will provide students with disabilities the supports and services indicated on their IEPs.
ValueCountFrequency (%)
this 437
 
6.7%
school 437
 
6.7%
will 437
 
6.7%
provide 437
 
6.7%
students 437
 
6.7%
with 437
 
6.7%
disabilities 437
 
6.7%
the 437
 
6.7%
supports 437
 
6.7%
and 437
 
6.7%
Other values (5) 2185
33.3%
2023-12-09T22:18:48.139872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6118
13.7%
i 5244
11.8%
s 4807
10.8%
e 3496
 
7.8%
t 3496
 
7.8%
d 2622
 
5.9%
o 2185
 
4.9%
h 2185
 
4.9%
l 1748
 
3.9%
n 1748
 
3.9%
Other values (13) 10925
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36271
81.4%
Space Separator 6118
 
13.7%
Uppercase Letter 1748
 
3.9%
Other Punctuation 437
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 5244
14.5%
s 4807
13.3%
e 3496
9.6%
t 3496
9.6%
d 2622
 
7.2%
o 2185
 
6.0%
h 2185
 
6.0%
l 1748
 
4.8%
n 1748
 
4.8%
r 1748
 
4.8%
Other values (7) 6992
19.3%
Uppercase Letter
ValueCountFrequency (%)
E 437
25.0%
P 437
25.0%
T 437
25.0%
I 437
25.0%
Space Separator
ValueCountFrequency (%)
6118
100.0%
Other Punctuation
ValueCountFrequency (%)
. 437
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38019
85.3%
Common 6555
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 5244
13.8%
s 4807
12.6%
e 3496
 
9.2%
t 3496
 
9.2%
d 2622
 
6.9%
o 2185
 
5.7%
h 2185
 
5.7%
l 1748
 
4.6%
n 1748
 
4.6%
r 1748
 
4.6%
Other values (11) 8740
23.0%
Common
ValueCountFrequency (%)
6118
93.3%
. 437
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44574
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6118
13.7%
i 5244
11.8%
s 4807
10.8%
e 3496
 
7.8%
t 3496
 
7.8%
d 2622
 
5.9%
o 2185
 
4.9%
h 2185
 
4.9%
l 1748
 
3.9%
n 1748
 
3.9%
Other values (13) 10925
24.5%
Distinct9
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size27.6 KiB
2023-12-09T22:18:48.307306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length70
Median length3
Mean length7.473684211
Min length3

Characters and Unicode

Total characters3266
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st rowESL
2nd rowESL, Transitional Bilingual Education: Chinese
3rd rowESL
4th rowESL
5th rowESL
ValueCountFrequency (%)
esl 437
70.1%
transitional 41
 
6.6%
bilingual 41
 
6.6%
education 41
 
6.6%
spanish 38
 
6.1%
chinese 14
 
2.2%
dual 4
 
0.6%
language 4
 
0.6%
haitian-creole 1
 
0.2%
arabic 1
 
0.2%
2023-12-09T22:18:48.601790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 478
14.6%
S 475
14.5%
L 441
13.5%
i 261
 
8.0%
n 222
 
6.8%
a 218
 
6.7%
186
 
5.7%
l 129
 
3.9%
s 93
 
2.8%
u 90
 
2.8%
Other values (19) 673
20.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1498
45.9%
Lowercase Letter 1481
45.3%
Space Separator 186
 
5.7%
Other Punctuation 100
 
3.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 261
17.6%
n 222
15.0%
a 218
14.7%
l 129
8.7%
s 93
 
6.3%
u 90
 
6.1%
t 83
 
5.6%
o 83
 
5.6%
h 52
 
3.5%
g 50
 
3.4%
Other values (6) 200
13.5%
Uppercase Letter
ValueCountFrequency (%)
E 478
31.9%
S 475
31.7%
L 441
29.4%
B 42
 
2.8%
T 41
 
2.7%
C 15
 
1.0%
D 4
 
0.3%
H 1
 
0.1%
A 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 55
55.0%
: 45
45.0%
Space Separator
ValueCountFrequency (%)
186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2979
91.2%
Common 287
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 478
16.0%
S 475
15.9%
L 441
14.8%
i 261
8.8%
n 222
7.5%
a 218
7.3%
l 129
 
4.3%
s 93
 
3.1%
u 90
 
3.0%
t 83
 
2.8%
Other values (15) 489
16.4%
Common
ValueCountFrequency (%)
186
64.8%
, 55
 
19.2%
: 45
 
15.7%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3266
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 478
14.6%
S 475
14.5%
L 441
13.5%
i 261
 
8.0%
n 222
 
6.8%
a 218
 
6.7%
186
 
5.7%
l 129
 
3.9%
s 93
 
2.8%
u 90
 
2.8%
Other values (19) 673
20.6%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size34.8 KiB
2023-12-09T22:18:48.776773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length23
Mean length24.25400458
Min length23

Characters and Unicode

Total characters10599
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFunctionally Accessible
2nd rowNot Functionally Accessible
3rd rowNot Functionally Accessible
4th rowFunctionally Accessible
5th rowNot Functionally Accessible
ValueCountFrequency (%)
functionally 437
43.2%
accessible 437
43.2%
not 137
 
13.6%
2023-12-09T22:18:49.090734image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 1311
12.4%
l 1311
12.4%
n 874
 
8.2%
i 874
 
8.2%
e 874
 
8.2%
s 874
 
8.2%
t 574
 
5.4%
o 574
 
5.4%
574
 
5.4%
F 437
 
4.1%
Other values (6) 2322
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9014
85.0%
Uppercase Letter 1011
 
9.5%
Space Separator 574
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 1311
14.5%
l 1311
14.5%
n 874
9.7%
i 874
9.7%
e 874
9.7%
s 874
9.7%
t 574
6.4%
o 574
6.4%
u 437
 
4.8%
a 437
 
4.8%
Other values (2) 874
9.7%
Uppercase Letter
ValueCountFrequency (%)
F 437
43.2%
A 437
43.2%
N 137
 
13.6%
Space Separator
ValueCountFrequency (%)
574
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10025
94.6%
Common 574
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 1311
13.1%
l 1311
13.1%
n 874
8.7%
i 874
8.7%
e 874
8.7%
s 874
8.7%
t 574
 
5.7%
o 574
 
5.7%
F 437
 
4.4%
u 437
 
4.4%
Other values (5) 1885
18.8%
Common
ValueCountFrequency (%)
574
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 1311
12.4%
l 1311
12.4%
n 874
 
8.2%
i 874
 
8.2%
e 874
 
8.2%
s 874
 
8.2%
t 574
 
5.4%
o 574
 
5.4%
574
 
5.4%
F 437
 
4.1%
Other values (6) 2322
21.9%
Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size24.9 KiB
2023-12-09T22:18:49.212894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.00228833
Min length1

Characters and Unicode

Total characters438
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row1
2nd row3
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 315
72.1%
2 51
 
11.7%
4 19
 
4.3%
3 16
 
3.7%
5 14
 
3.2%
6 7
 
1.6%
7 7
 
1.6%
8 6
 
1.4%
9 1
 
0.2%
10 1
 
0.2%
2023-12-09T22:18:49.451010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 316
72.1%
2 51
 
11.6%
4 19
 
4.3%
3 16
 
3.7%
5 14
 
3.2%
6 7
 
1.6%
7 7
 
1.6%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 438
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 316
72.1%
2 51
 
11.6%
4 19
 
4.3%
3 16
 
3.7%
5 14
 
3.2%
6 7
 
1.6%
7 7
 
1.6%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 438
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 316
72.1%
2 51
 
11.6%
4 19
 
4.3%
3 16
 
3.7%
5 14
 
3.2%
6 7
 
1.6%
7 7
 
1.6%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 316
72.1%
2 51
 
11.6%
4 19
 
4.3%
3 16
 
3.7%
5 14
 
3.2%
6 7
 
1.6%
7 7
 
1.6%
8 6
 
1.4%
9 1
 
0.2%
0 1
 
0.2%
Distinct82
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size53.3 KiB
2023-12-09T22:18:49.797108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length297
Median length269
Mean length67.29519451
Min length14

Characters and Unicode

Total characters29408
Distinct characters72
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)12.8%

Sample

1st rowPriority to continuing 8th graders
2nd rowOpen to New York City residents
3rd rowPriority to continuing 8th graders
4th rowPriority to District 1 students or residents
5th rowPriority to continuing 8th graders
ValueCountFrequency (%)
to 463
 
9.9%
residents 369
 
7.9%
priority 306
 
6.5%
or 262
 
5.6%
students 235
 
5.0%
who 206
 
4.4%
new 180
 
3.8%
york 180
 
3.8%
city 179
 
3.8%
an 177
 
3.8%
Other values (189) 2123
45.4%
2023-12-09T22:18:50.359168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4243
14.4%
t 2907
9.9%
n 2496
 
8.5%
o 2442
 
8.3%
e 2400
 
8.2%
i 2392
 
8.1%
r 2147
 
7.3%
s 2086
 
7.1%
a 1041
 
3.5%
d 1010
 
3.4%
Other values (62) 6244
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23003
78.2%
Space Separator 4243
 
14.4%
Uppercase Letter 1799
 
6.1%
Decimal Number 173
 
0.6%
Other Punctuation 152
 
0.5%
Dash Punctuation 22
 
0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Initial Punctuation 1
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2907
12.6%
n 2496
10.9%
o 2442
10.6%
e 2400
10.4%
i 2392
10.4%
r 2147
9.3%
s 2086
9.1%
a 1041
 
4.5%
d 1010
 
4.4%
y 672
 
2.9%
Other values (15) 3410
14.8%
Uppercase Letter
ValueCountFrequency (%)
P 310
17.2%
Y 204
11.3%
N 203
11.3%
C 181
10.1%
B 140
7.8%
O 132
7.3%
E 127
7.1%
S 93
 
5.2%
L 91
 
5.1%
T 54
 
3.0%
Other values (14) 264
14.7%
Decimal Number
ValueCountFrequency (%)
8 69
39.9%
1 21
 
12.1%
2 20
 
11.6%
5 14
 
8.1%
3 14
 
8.1%
0 11
 
6.4%
6 9
 
5.2%
9 6
 
3.5%
4 5
 
2.9%
7 4
 
2.3%
Other Punctuation
ValueCountFrequency (%)
: 59
38.8%
. 57
37.5%
, 25
16.4%
/ 5
 
3.3%
% 2
 
1.3%
& 2
 
1.3%
; 2
 
1.3%
Space Separator
ValueCountFrequency (%)
4243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24802
84.3%
Common 4606
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2907
11.7%
n 2496
10.1%
o 2442
9.8%
e 2400
9.7%
i 2392
9.6%
r 2147
8.7%
s 2086
8.4%
a 1041
 
4.2%
d 1010
 
4.1%
y 672
 
2.7%
Other values (39) 5209
21.0%
Common
ValueCountFrequency (%)
4243
92.1%
8 69
 
1.5%
: 59
 
1.3%
. 57
 
1.2%
, 25
 
0.5%
- 22
 
0.5%
1 21
 
0.5%
2 20
 
0.4%
5 14
 
0.3%
3 14
 
0.3%
Other values (13) 62
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29406
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4243
14.4%
t 2907
9.9%
n 2496
 
8.5%
o 2442
 
8.3%
e 2400
 
8.2%
i 2392
 
8.1%
r 2147
 
7.3%
s 2086
 
7.1%
a 1041
 
3.5%
d 1010
 
3.4%
Other values (60) 6242
21.2%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%

priority02
Text

MISSING 

Distinct73
Distinct (%)20.4%
Missing80
Missing (%)18.3%
Memory size43.7 KiB
2023-12-09T22:18:50.640029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length330
Median length277
Mean length60.03081232
Min length31

Characters and Unicode

Total characters21431
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)16.2%

Sample

1st rowThen to Manhattan students or residents who attend an information session
2nd rowFor M35B only: Open only to students whose home language is Chinese (Mandarin)
3rd rowThen to New York City residents
4th rowThen to Manhattan students or residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 408
 
11.0%
residents 352
 
9.5%
then 332
 
9.0%
new 256
 
6.9%
york 256
 
6.9%
city 256
 
6.9%
who 193
 
5.2%
information 173
 
4.7%
session 173
 
4.7%
an 173
 
4.7%
Other values (168) 1136
30.6%
2023-12-09T22:18:51.113075image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3351
15.6%
n 2033
9.5%
e 2022
9.4%
t 2000
9.3%
o 1793
 
8.4%
s 1575
 
7.3%
i 1401
 
6.5%
r 1201
 
5.6%
a 777
 
3.6%
d 755
 
3.5%
Other values (56) 4523
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16329
76.2%
Space Separator 3351
 
15.6%
Uppercase Letter 1457
 
6.8%
Decimal Number 160
 
0.7%
Other Punctuation 125
 
0.6%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 2033
12.5%
e 2022
12.4%
t 2000
12.2%
o 1793
11.0%
s 1575
9.6%
i 1401
8.6%
r 1201
7.4%
a 777
 
4.8%
d 755
 
4.6%
h 627
 
3.8%
Other values (14) 2145
13.1%
Uppercase Letter
ValueCountFrequency (%)
T 335
23.0%
C 261
17.9%
Y 258
17.7%
N 256
17.6%
B 61
 
4.2%
P 54
 
3.7%
F 41
 
2.8%
M 27
 
1.9%
D 25
 
1.7%
Q 24
 
1.6%
Other values (14) 115
 
7.9%
Decimal Number
ValueCountFrequency (%)
8 31
19.4%
2 23
14.4%
1 21
13.1%
5 18
11.2%
3 16
10.0%
6 15
9.4%
9 11
 
6.9%
0 11
 
6.9%
7 8
 
5.0%
4 6
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 65
52.0%
: 41
32.8%
, 16
 
12.8%
; 3
 
2.4%
Space Separator
ValueCountFrequency (%)
3351
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17786
83.0%
Common 3645
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 2033
11.4%
e 2022
11.4%
t 2000
11.2%
o 1793
10.1%
s 1575
8.9%
i 1401
 
7.9%
r 1201
 
6.8%
a 777
 
4.4%
d 755
 
4.2%
h 627
 
3.5%
Other values (38) 3602
20.3%
Common
ValueCountFrequency (%)
3351
91.9%
. 65
 
1.8%
: 41
 
1.1%
8 31
 
0.9%
2 23
 
0.6%
1 21
 
0.6%
5 18
 
0.5%
3 16
 
0.4%
, 16
 
0.4%
6 15
 
0.4%
Other values (8) 48
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21430
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3351
15.6%
n 2033
9.5%
e 2022
9.4%
t 2000
9.3%
o 1793
 
8.4%
s 1575
 
7.3%
i 1401
 
6.5%
r 1201
 
5.6%
a 777
 
3.6%
d 755
 
3.5%
Other values (55) 4522
21.1%
Punctuation
ValueCountFrequency (%)
1
100.0%

priority03
Text

MISSING 

Distinct31
Distinct (%)13.3%
Missing204
Missing (%)46.7%
Memory size30.7 KiB
2023-12-09T22:18:51.378073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length364
Median length240
Mean length49.35622318
Min length31

Characters and Unicode

Total characters11500
Distinct characters63
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)7.7%

Sample

1st rowThen to New York City residents who attend an information session
2nd rowThen to New York City residents
3rd rowThen to Manhattan students or residents
4th rowThen to Manhattan students or residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 242
 
12.3%
residents 219
 
11.1%
then 218
 
11.0%
students 161
 
8.2%
or 138
 
7.0%
york 82
 
4.2%
city 82
 
4.2%
new 82
 
4.2%
who 62
 
3.1%
bronx 56
 
2.8%
Other values (92) 631
32.0%
2023-12-09T22:18:51.804637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1740
15.1%
e 1221
10.6%
n 1134
9.9%
t 1112
9.7%
s 956
8.3%
o 928
8.1%
r 710
 
6.2%
i 535
 
4.7%
d 503
 
4.4%
a 356
 
3.1%
Other values (53) 2305
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8924
77.6%
Space Separator 1740
 
15.1%
Uppercase Letter 744
 
6.5%
Other Punctuation 46
 
0.4%
Decimal Number 39
 
0.3%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1221
13.7%
n 1134
12.7%
t 1112
12.5%
s 956
10.7%
o 928
10.4%
r 710
8.0%
i 535
6.0%
d 503
5.6%
a 356
 
4.0%
h 350
 
3.9%
Other values (14) 1119
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 219
29.4%
B 92
12.4%
C 86
 
11.6%
N 82
 
11.0%
Y 82
 
11.0%
M 28
 
3.8%
F 26
 
3.5%
Q 25
 
3.4%
P 21
 
2.8%
Z 16
 
2.2%
Other values (12) 67
 
9.0%
Decimal Number
ValueCountFrequency (%)
5 9
23.1%
1 6
15.4%
2 6
15.4%
4 5
12.8%
0 4
10.3%
7 3
 
7.7%
6 2
 
5.1%
3 2
 
5.1%
9 2
 
5.1%
Other Punctuation
ValueCountFrequency (%)
: 25
54.3%
. 17
37.0%
, 2
 
4.3%
% 2
 
4.3%
Space Separator
ValueCountFrequency (%)
1740
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9668
84.1%
Common 1832
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1221
12.6%
n 1134
11.7%
t 1112
11.5%
s 956
9.9%
o 928
9.6%
r 710
 
7.3%
i 535
 
5.5%
d 503
 
5.2%
a 356
 
3.7%
h 350
 
3.6%
Other values (36) 1863
19.3%
Common
ValueCountFrequency (%)
1740
95.0%
: 25
 
1.4%
. 17
 
0.9%
5 9
 
0.5%
1 6
 
0.3%
2 6
 
0.3%
4 5
 
0.3%
0 4
 
0.2%
7 3
 
0.2%
( 3
 
0.2%
Other values (7) 14
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1740
15.1%
e 1221
10.6%
n 1134
9.9%
t 1112
9.7%
s 956
8.3%
o 928
8.1%
r 710
 
6.2%
i 535
 
4.7%
d 503
 
4.4%
a 356
 
3.1%
Other values (53) 2305
20.0%

priority04
Text

MISSING 

Distinct22
Distinct (%)13.0%
Missing268
Missing (%)61.3%
Memory size24.0 KiB
2023-12-09T22:18:52.096008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length300
Median length31
Mean length37.10059172
Min length31

Characters and Unicode

Total characters6270
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)8.9%

Sample

1st rowThen to Manhattan students or residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to New York City residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 172
14.8%
then 167
14.4%
residents 165
14.2%
new 135
11.6%
york 135
11.6%
city 135
11.6%
students 36
 
3.1%
or 30
 
2.6%
who 14
 
1.2%
bronx 11
 
0.9%
Other values (58) 163
14.0%
2023-12-09T22:18:52.538380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
994
15.9%
e 729
11.6%
t 615
9.8%
n 487
 
7.8%
s 462
 
7.4%
o 437
 
7.0%
r 392
 
6.3%
i 372
 
5.9%
d 232
 
3.7%
h 198
 
3.2%
Other values (46) 1352
21.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4595
73.3%
Space Separator 994
 
15.9%
Uppercase Letter 632
 
10.1%
Decimal Number 34
 
0.5%
Other Punctuation 15
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 729
15.9%
t 615
13.4%
n 487
10.6%
s 462
10.1%
o 437
9.5%
r 392
8.5%
i 372
8.1%
d 232
 
5.0%
h 198
 
4.3%
y 151
 
3.3%
Other values (14) 520
11.3%
Uppercase Letter
ValueCountFrequency (%)
T 167
26.4%
Y 135
21.4%
N 135
21.4%
C 135
21.4%
B 15
 
2.4%
D 10
 
1.6%
F 8
 
1.3%
M 6
 
0.9%
Q 3
 
0.5%
K 3
 
0.5%
Other values (8) 15
 
2.4%
Decimal Number
ValueCountFrequency (%)
2 7
20.6%
3 6
17.6%
1 6
17.6%
6 5
14.7%
5 4
11.8%
8 2
 
5.9%
9 1
 
2.9%
0 1
 
2.9%
7 1
 
2.9%
4 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
: 6
40.0%
. 5
33.3%
, 4
26.7%
Space Separator
ValueCountFrequency (%)
994
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5227
83.4%
Common 1043
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 729
13.9%
t 615
11.8%
n 487
9.3%
s 462
8.8%
o 437
 
8.4%
r 392
 
7.5%
i 372
 
7.1%
d 232
 
4.4%
h 198
 
3.8%
T 167
 
3.2%
Other values (32) 1136
21.7%
Common
ValueCountFrequency (%)
994
95.3%
2 7
 
0.7%
3 6
 
0.6%
: 6
 
0.6%
1 6
 
0.6%
6 5
 
0.5%
. 5
 
0.5%
5 4
 
0.4%
, 4
 
0.4%
8 2
 
0.2%
Other values (4) 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
994
15.9%
e 729
11.6%
t 615
9.8%
n 487
 
7.8%
s 462
 
7.4%
o 437
 
7.0%
r 392
 
6.3%
i 372
 
5.9%
d 232
 
3.7%
h 198
 
3.2%
Other values (46) 1352
21.6%

priority05
Text

MISSING 

Distinct9
Distinct (%)23.7%
Missing399
Missing (%)91.3%
Memory size16.0 KiB
2023-12-09T22:18:52.758512image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length62
Median length57.5
Mean length35.42105263
Min length31

Characters and Unicode

Total characters1346
Distinct characters35
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)10.5%

Sample

1st rowThen to New York City residents
2nd rowThen to Manhattan students or residents
3rd rowThen to Manhattan students or residents
4th rowThen to Manhattan students or residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 38
16.0%
to 38
16.0%
residents 37
15.5%
new 19
8.0%
york 19
8.0%
city 19
8.0%
students 19
8.0%
or 18
7.6%
brooklyn 6
 
2.5%
manhattan 4
 
1.7%
Other values (17) 21
8.8%
2023-12-09T22:18:55.297967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200
14.9%
e 160
11.9%
t 149
11.1%
s 119
8.8%
n 116
8.6%
o 92
 
6.8%
r 89
 
6.6%
i 65
 
4.8%
d 58
 
4.3%
h 46
 
3.4%
Other values (25) 252
18.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1023
76.0%
Space Separator 200
 
14.9%
Uppercase Letter 113
 
8.4%
Decimal Number 9
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 160
15.6%
t 149
14.6%
s 119
11.6%
n 116
11.3%
o 92
9.0%
r 89
8.7%
i 65
6.4%
d 58
 
5.7%
h 46
 
4.5%
k 25
 
2.4%
Other values (10) 104
10.2%
Uppercase Letter
ValueCountFrequency (%)
T 38
33.6%
Y 19
16.8%
C 19
16.8%
N 19
16.8%
B 9
 
8.0%
M 4
 
3.5%
D 3
 
2.7%
Q 2
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
3 2
22.2%
7 1
 
11.1%
4 1
 
11.1%
0 1
 
11.1%
Space Separator
ValueCountFrequency (%)
200
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1136
84.4%
Common 210
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 160
14.1%
t 149
13.1%
s 119
10.5%
n 116
10.2%
o 92
8.1%
r 89
7.8%
i 65
 
5.7%
d 58
 
5.1%
h 46
 
4.0%
T 38
 
3.3%
Other values (18) 204
18.0%
Common
ValueCountFrequency (%)
200
95.2%
2 4
 
1.9%
3 2
 
1.0%
7 1
 
0.5%
4 1
 
0.5%
, 1
 
0.5%
0 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
200
14.9%
e 160
11.9%
t 149
11.1%
s 119
8.8%
n 116
8.6%
o 92
 
6.8%
r 89
 
6.6%
i 65
 
4.8%
d 58
 
4.3%
h 46
 
3.4%
Other values (25) 252
18.7%

priority06
Text

MISSING 

Distinct5
Distinct (%)26.3%
Missing418
Missing (%)95.7%
Memory size14.8 KiB
2023-12-09T22:18:55.489646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length31
Mean length32.05263158
Min length31

Characters and Unicode

Total characters609
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)21.1%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
4th rowThen to Manhattan students or residents
5th rowThen to New York City residents
ValueCountFrequency (%)
then 19
16.7%
to 19
16.7%
residents 19
16.7%
new 16
14.0%
york 16
14.0%
city 16
14.0%
students 3
 
2.6%
or 3
 
2.6%
brooklyn 1
 
0.9%
queens 1
 
0.9%
2023-12-09T22:18:55.820020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
15.6%
e 78
12.8%
t 62
10.2%
n 45
 
7.4%
s 45
 
7.4%
o 40
 
6.6%
r 39
 
6.4%
i 35
 
5.7%
d 22
 
3.6%
h 20
 
3.3%
Other values (14) 128
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 445
73.1%
Space Separator 95
 
15.6%
Uppercase Letter 69
 
11.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 78
17.5%
t 62
13.9%
n 45
10.1%
s 45
10.1%
o 40
9.0%
r 39
8.8%
i 35
7.9%
d 22
 
4.9%
h 20
 
4.5%
k 17
 
3.8%
Other values (6) 42
9.4%
Uppercase Letter
ValueCountFrequency (%)
T 19
27.5%
N 16
23.2%
Y 16
23.2%
C 15
21.7%
B 1
 
1.4%
Q 1
 
1.4%
M 1
 
1.4%
Space Separator
ValueCountFrequency (%)
95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 514
84.4%
Common 95
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 78
15.2%
t 62
12.1%
n 45
8.8%
s 45
8.8%
o 40
 
7.8%
r 39
 
7.6%
i 35
 
6.8%
d 22
 
4.3%
h 20
 
3.9%
T 19
 
3.7%
Other values (13) 109
21.2%
Common
ValueCountFrequency (%)
95
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 609
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
15.6%
e 78
12.8%
t 62
10.2%
n 45
 
7.4%
s 45
 
7.4%
o 40
 
6.6%
r 39
 
6.4%
i 35
 
5.7%
d 22
 
3.6%
h 20
 
3.3%
Other values (14) 128
21.0%

priority07
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)33.3%
Missing434
Missing (%)99.3%
Memory size13.9 KiB
2023-12-09T22:18:56.009287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters93
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThen to New York City residents
2nd rowThen to New York City residents
3rd rowThen to New York City residents
ValueCountFrequency (%)
then 3
16.7%
to 3
16.7%
new 3
16.7%
york 3
16.7%
city 3
16.7%
residents 3
16.7%
2023-12-09T22:18:56.322483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
16.1%
e 12
12.9%
t 9
9.7%
n 6
 
6.5%
o 6
 
6.5%
s 6
 
6.5%
i 6
 
6.5%
r 6
 
6.5%
T 3
 
3.2%
C 3
 
3.2%
Other values (7) 21
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 66
71.0%
Space Separator 15
 
16.1%
Uppercase Letter 12
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12
18.2%
t 9
13.6%
n 6
9.1%
o 6
9.1%
s 6
9.1%
i 6
9.1%
r 6
9.1%
y 3
 
4.5%
w 3
 
4.5%
k 3
 
4.5%
Other values (2) 6
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 3
25.0%
C 3
25.0%
Y 3
25.0%
N 3
25.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 78
83.9%
Common 15
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12
15.4%
t 9
11.5%
n 6
 
7.7%
o 6
 
7.7%
s 6
 
7.7%
i 6
 
7.7%
r 6
 
7.7%
T 3
 
3.8%
C 3
 
3.8%
y 3
 
3.8%
Other values (6) 18
23.1%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
16.1%
e 12
12.9%
t 9
9.7%
n 6
 
6.5%
o 6
 
6.5%
s 6
 
6.5%
i 6
 
6.5%
r 6
 
6.5%
T 3
 
3.2%
C 3
 
3.2%
Other values (7) 21
22.6%

priority08
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing437
Missing (%)100.0%
Memory size3.5 KiB

priority09
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing437
Missing (%)100.0%
Memory size3.5 KiB

priority10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing437
Missing (%)100.0%
Memory size3.5 KiB
Distinct257
Distinct (%)58.9%
Missing1
Missing (%)0.2%
Memory size28.2 KiB
2023-12-09T22:18:56.674180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.873853211
Min length7

Characters and Unicode

Total characters3869
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)40.1%

Sample

1st row40.713684
2nd row40.712399
3rd row40.729589
4th row40.720581
5th row40.718895
ValueCountFrequency (%)
40.82229 6
 
1.4%
40.875953 6
 
1.4%
40.840702 6
 
1.4%
40.840422 6
 
1.4%
40.860043 6
 
1.4%
40.870293 5
 
1.1%
40.735494 5
 
1.1%
40.774351 5
 
1.1%
40.765184 5
 
1.1%
40.649787 5
 
1.1%
Other values (247) 381
87.4%
2023-12-09T22:18:57.174189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 689
17.8%
0 584
15.1%
. 436
11.3%
7 363
9.4%
8 338
8.7%
6 316
8.2%
5 248
 
6.4%
1 231
 
6.0%
9 230
 
5.9%
3 224
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3433
88.7%
Other Punctuation 436
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 689
20.1%
0 584
17.0%
7 363
10.6%
8 338
9.8%
6 316
9.2%
5 248
 
7.2%
1 231
 
6.7%
9 230
 
6.7%
3 224
 
6.5%
2 210
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3869
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 689
17.8%
0 584
15.1%
. 436
11.3%
7 363
9.4%
8 338
8.7%
6 316
8.2%
5 248
 
6.4%
1 231
 
6.0%
9 230
 
5.9%
3 224
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 689
17.8%
0 584
15.1%
. 436
11.3%
7 363
9.4%
8 338
8.7%
6 316
8.2%
5 248
 
6.4%
1 231
 
6.0%
9 230
 
5.9%
3 224
 
5.8%
Distinct256
Distinct (%)58.7%
Missing1
Missing (%)0.2%
Memory size28.6 KiB
2023-12-09T22:18:57.539708image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.876146789
Min length8

Characters and Unicode

Total characters4306
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)39.7%

Sample

1st row-73.986336
2nd row-73.984497
3rd row-73.982555
4th row-73.985645
5th row-73.979308
ValueCountFrequency (%)
73.838545 6
 
1.4%
73.86197 6
 
1.4%
73.856167 6
 
1.4%
73.91091 6
 
1.4%
73.888267 6
 
1.4%
73.984753 5
 
1.1%
73.95855 5
 
1.1%
73.989337 5
 
1.1%
73.98577 5
 
1.1%
73.987659 5
 
1.1%
Other values (246) 381
87.4%
2023-12-09T22:18:58.029518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 697
16.2%
3 616
14.3%
9 459
10.7%
- 436
10.1%
. 436
10.1%
8 356
8.3%
1 234
 
5.4%
5 229
 
5.3%
2 226
 
5.2%
4 220
 
5.1%
Other values (2) 397
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3434
79.7%
Dash Punctuation 436
 
10.1%
Other Punctuation 436
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 697
20.3%
3 616
17.9%
9 459
13.4%
8 356
10.4%
1 234
 
6.8%
5 229
 
6.7%
2 226
 
6.6%
4 220
 
6.4%
6 202
 
5.9%
0 195
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 436
100.0%
Other Punctuation
ValueCountFrequency (%)
. 436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 697
16.2%
3 616
14.3%
9 459
10.7%
- 436
10.1%
. 436
10.1%
8 356
8.3%
1 234
 
5.4%
5 229
 
5.3%
2 226
 
5.2%
4 220
 
5.1%
Other values (2) 397
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 697
16.2%
3 616
14.3%
9 459
10.7%
- 436
10.1%
. 436
10.1%
8 356
8.3%
1 234
 
5.4%
5 229
 
5.3%
2 226
 
5.2%
4 220
 
5.1%
Other values (2) 397
9.2%
Distinct18
Distinct (%)4.1%
Missing1
Missing (%)0.2%
Memory size25.0 KiB
2023-12-09T22:18:58.223142image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.270642202
Min length1

Characters and Unicode

Total characters554
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3
ValueCountFrequency (%)
1 49
11.2%
4 43
9.9%
3 41
9.4%
2 37
8.5%
9 33
 
7.6%
6 32
 
7.3%
12 31
 
7.1%
5 28
 
6.4%
8 28
 
6.4%
7 27
 
6.2%
Other values (8) 87
20.0%
2023-12-09T22:18:58.531723image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 187
33.8%
2 68
 
12.3%
4 57
 
10.3%
3 57
 
10.3%
6 36
 
6.5%
8 35
 
6.3%
9 33
 
6.0%
5 31
 
5.6%
7 31
 
5.6%
0 19
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 554
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 187
33.8%
2 68
 
12.3%
4 57
 
10.3%
3 57
 
10.3%
6 36
 
6.5%
8 35
 
6.3%
9 33
 
6.0%
5 31
 
5.6%
7 31
 
5.6%
0 19
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 554
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 187
33.8%
2 68
 
12.3%
4 57
 
10.3%
3 57
 
10.3%
6 36
 
6.5%
8 35
 
6.3%
9 33
 
6.0%
5 31
 
5.6%
7 31
 
5.6%
0 19
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 187
33.8%
2 68
 
12.3%
4 57
 
10.3%
3 57
 
10.3%
6 36
 
6.5%
8 35
 
6.3%
9 33
 
6.0%
5 31
 
5.6%
7 31
 
5.6%
0 19
 
3.4%
Distinct51
Distinct (%)11.7%
Missing1
Missing (%)0.2%
Memory size25.2 KiB
2023-12-09T22:18:58.780128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.756880734
Min length1

Characters and Unicode

Total characters766
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row2
ValueCountFrequency (%)
3 23
 
5.3%
33 21
 
4.8%
1 20
 
4.6%
17 20
 
4.6%
16 20
 
4.6%
26 16
 
3.7%
2 16
 
3.7%
8 15
 
3.4%
18 14
 
3.2%
15 14
 
3.2%
Other values (41) 257
58.9%
2023-12-09T22:18:59.159605image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 171
22.3%
3 146
19.1%
2 106
13.8%
4 88
11.5%
6 62
 
8.1%
7 53
 
6.9%
5 44
 
5.7%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 766
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
22.3%
3 146
19.1%
2 106
13.8%
4 88
11.5%
6 62
 
8.1%
7 53
 
6.9%
5 44
 
5.7%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 766
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 171
22.3%
3 146
19.1%
2 106
13.8%
4 88
11.5%
6 62
 
8.1%
7 53
 
6.9%
5 44
 
5.7%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 766
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 171
22.3%
3 146
19.1%
2 106
13.8%
4 88
11.5%
6 62
 
8.1%
7 53
 
6.9%
5 44
 
5.7%
8 40
 
5.2%
0 33
 
4.3%
9 23
 
3.0%
Distinct203
Distinct (%)46.6%
Missing1
Missing (%)0.2%
Memory size25.7 KiB
2023-12-09T22:18:59.668004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.97706422
Min length1

Characters and Unicode

Total characters1298
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)25.2%

Sample

1st row201
2nd row202
3rd row34
4th row3001
5th row2201
ValueCountFrequency (%)
409 10
 
2.3%
135 9
 
2.1%
194 7
 
1.6%
16 7
 
1.6%
151 7
 
1.6%
56 7
 
1.6%
387 6
 
1.4%
225 6
 
1.4%
213 6
 
1.4%
179 6
 
1.4%
Other values (193) 365
83.7%
2023-12-09T22:19:00.318144image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 264
20.3%
3 155
11.9%
2 138
10.6%
0 129
9.9%
5 123
9.5%
9 118
9.1%
4 107
8.2%
7 97
 
7.5%
6 85
 
6.5%
8 82
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1298
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 264
20.3%
3 155
11.9%
2 138
10.6%
0 129
9.9%
5 123
9.5%
9 118
9.1%
4 107
8.2%
7 97
 
7.5%
6 85
 
6.5%
8 82
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1298
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 264
20.3%
3 155
11.9%
2 138
10.6%
0 129
9.9%
5 123
9.5%
9 118
9.1%
4 107
8.2%
7 97
 
7.5%
6 85
 
6.5%
8 82
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 264
20.3%
3 155
11.9%
2 138
10.6%
0 129
9.9%
5 123
9.5%
9 118
9.1%
4 107
8.2%
7 97
 
7.5%
6 85
 
6.5%
8 82
 
6.3%

bin
Text

Distinct256
Distinct (%)58.9%
Missing2
Missing (%)0.5%
Memory size27.4 KiB
2023-12-09T22:19:00.773035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3045
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)40.0%

Sample

1st row1003223
2nd row1003214
3rd row1005974
4th row1004323
5th row1004070
ValueCountFrequency (%)
2011810 6
 
1.4%
2057045 6
 
1.4%
2074045 6
 
1.4%
2007806 6
 
1.4%
2022205 6
 
1.4%
1030343 5
 
1.1%
1013096 5
 
1.1%
3186454 5
 
1.1%
2050179 5
 
1.1%
3336215 5
 
1.1%
Other values (246) 380
87.4%
2023-12-09T22:19:01.347919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 596
19.6%
1 386
12.7%
3 376
12.3%
2 349
11.5%
4 319
10.5%
5 240
7.9%
8 218
 
7.2%
7 202
 
6.6%
6 200
 
6.6%
9 159
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3045
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 596
19.6%
1 386
12.7%
3 376
12.3%
2 349
11.5%
4 319
10.5%
5 240
7.9%
8 218
 
7.2%
7 202
 
6.6%
6 200
 
6.6%
9 159
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3045
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 596
19.6%
1 386
12.7%
3 376
12.3%
2 349
11.5%
4 319
10.5%
5 240
7.9%
8 218
 
7.2%
7 202
 
6.6%
6 200
 
6.6%
9 159
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3045
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 596
19.6%
1 386
12.7%
3 376
12.3%
2 349
11.5%
4 319
10.5%
5 240
7.9%
8 218
 
7.2%
7 202
 
6.6%
6 200
 
6.6%
9 159
 
5.2%

bbl
Text

Distinct254
Distinct (%)58.4%
Missing2
Missing (%)0.5%
Memory size28.6 KiB
2023-12-09T22:19:01.613283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4350
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)39.3%

Sample

1st row1002690041
2nd row1002590044
3rd row1004390017
4th row1003540080
5th row1003350001
ValueCountFrequency (%)
2046330040 6
 
1.4%
2028170002 6
 
1.4%
2036040039 6
 
1.4%
2030590001 6
 
1.4%
2053680001 6
 
1.4%
1008720057 5
 
1.1%
1004080030 5
 
1.1%
1010790029 5
 
1.1%
3040940001 5
 
1.1%
1011570025 5
 
1.1%
Other values (244) 380
87.4%
2023-12-09T22:19:01.986091image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1779
40.9%
1 625
 
14.4%
2 407
 
9.4%
3 377
 
8.7%
4 293
 
6.7%
5 198
 
4.6%
8 185
 
4.3%
6 172
 
4.0%
7 162
 
3.7%
9 152
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4350
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1779
40.9%
1 625
 
14.4%
2 407
 
9.4%
3 377
 
8.7%
4 293
 
6.7%
5 198
 
4.6%
8 185
 
4.3%
6 172
 
4.0%
7 162
 
3.7%
9 152
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1779
40.9%
1 625
 
14.4%
2 407
 
9.4%
3 377
 
8.7%
4 293
 
6.7%
5 198
 
4.6%
8 185
 
4.3%
6 172
 
4.0%
7 162
 
3.7%
9 152
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1779
40.9%
1 625
 
14.4%
2 407
 
9.4%
3 377
 
8.7%
4 293
 
6.7%
5 198
 
4.6%
8 185
 
4.3%
6 172
 
4.0%
7 162
 
3.7%
9 152
 
3.5%

nta
Text

Distinct118
Distinct (%)27.1%
Missing1
Missing (%)0.2%
Memory size56.4 KiB
2023-12-09T22:19:02.301234image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters32700
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)7.6%

Sample

1st rowLower East Side
2nd rowLower East Side
3rd rowEast Village
4th rowChinatown
5th rowLower East Side
ValueCountFrequency (%)
east 42
 
4.2%
park 37
 
3.7%
north 34
 
3.4%
heights 28
 
2.8%
village 27
 
2.7%
south 25
 
2.5%
hill 25
 
2.5%
west 20
 
2.0%
square 19
 
1.9%
hills 15
 
1.5%
Other values (164) 740
73.1%
2023-12-09T22:19:02.724041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24059
73.6%
e 707
 
2.2%
a 647
 
2.0%
o 640
 
2.0%
r 606
 
1.9%
n 594
 
1.8%
l 556
 
1.7%
t 550
 
1.7%
i 522
 
1.6%
s 440
 
1.3%
Other values (45) 3379
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 24059
73.6%
Lowercase Letter 6946
 
21.2%
Uppercase Letter 1367
 
4.2%
Dash Punctuation 314
 
1.0%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 707
10.2%
a 647
9.3%
o 640
9.2%
r 606
8.7%
n 594
8.6%
l 556
 
8.0%
t 550
 
7.9%
i 522
 
7.5%
s 440
 
6.3%
h 238
 
3.4%
Other values (15) 1446
20.8%
Uppercase Letter
ValueCountFrequency (%)
H 185
13.5%
C 158
11.6%
B 152
11.1%
S 119
 
8.7%
M 92
 
6.7%
P 91
 
6.7%
E 63
 
4.6%
N 61
 
4.5%
W 57
 
4.2%
V 55
 
4.0%
Other values (14) 334
24.4%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
' 1
 
25.0%
Space Separator
ValueCountFrequency (%)
24059
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 314
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24387
74.6%
Latin 8313
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 707
 
8.5%
a 647
 
7.8%
o 640
 
7.7%
r 606
 
7.3%
n 594
 
7.1%
l 556
 
6.7%
t 550
 
6.6%
i 522
 
6.3%
s 440
 
5.3%
h 238
 
2.9%
Other values (39) 2813
33.8%
Common
ValueCountFrequency (%)
24059
98.7%
- 314
 
1.3%
( 5
 
< 0.1%
) 5
 
< 0.1%
. 3
 
< 0.1%
' 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24059
73.6%
e 707
 
2.2%
a 647
 
2.0%
o 640
 
2.0%
r 606
 
1.9%
n 594
 
1.8%
l 556
 
1.7%
t 550
 
1.7%
i 522
 
1.6%
s 440
 
1.3%
Other values (45) 3379
 
10.3%